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null | {
"abstract": " We study a connection between mapping spaces of bimodules and of\ninfinitesimal bimodules over an operad. As main application and motivation of\nour work, we produce an explicit delooping of the manifold calculus tower\nassociated to the space of smooth maps $D^{m}\\rightarrow D^{n}$ pf discs,\n$n\\geq m$, avoiding any given multisingularity and coinciding with the standard\ninclusion near $\\partial D^{m}$. In particular, we give a new proof of the\ndelooping of the space of disc embeddings in terms of little discs operads maps\nwith the advantage that it can be applied to more general mapping spaces.\n",
"title": "Delooping the functor calculus tower"
} | null | null | null | null | true | null | 18301 | null | Default | null | null |
null | {
"abstract": " Area law violations for entanglement entropy in the form of a square root has\nrecently been studied for one-dimensional frustration-free quantum systems\nbased on the Motzkin walks and their variations. Here we consider a Motzkin\nwalk with a different Hilbert space on each step of the walk spanned by\nelements of a {\\it Symmetric Inverse Semigroup} with the direction of each step\ngoverned by its algebraic structure. This change alters the number of paths\nallowed in the Motzkin walk and introduces a ground state degeneracy sensitive\nto boundary perturbations. We study the frustration-free spin chains based on\nthree symmetric inverse semigroups, $\\cS^3_1$, $\\cS^3_2$ and $\\cS^2_1$. The\nsystem based on $\\cS^3_1$ and $\\cS^3_2$ provide examples of quantum phase\ntransitions in one dimensions with the former exhibiting a transition between\nthe area law and a logarithmic violation of the area law and the latter\nproviding an example of transition from logarithmic scaling to a square root\nscaling in the system size, mimicking a colored $\\cS^3_1$ system. The system\nwith $\\cS^2_1$ is much simpler and produces states that continue to obey the\narea law.\n",
"title": "Area Law Violations and Quantum Phase Transitions in Modified Motzkin Walk Spin Chains"
} | null | null | null | null | true | null | 18302 | null | Default | null | null |
null | {
"abstract": " To guarantee the integrity and security of data transmitted through the\nInternet, hash functions are fundamental tools. But recent researches have\nshown that security flaws exist in the most widely used hash functions. So a\nnew way to improve their security performance is urgently demanded. In this\narticle, we propose new hash functions based on chaotic iterations, which have\nchaotic properties as defined by Devaney. The corresponding diffusion and\nconfusion analyzes are provided and a comparative study between the proposed\nhash functions is carried out, to make their use more applicable in any\nsecurity context.\n",
"title": "Diffusion and confusion of chaotic iteration based hash functions"
} | null | null | [
"Computer Science",
"Physics"
]
| null | true | null | 18303 | null | Validated | null | null |
null | {
"abstract": " We present a new large-scale (4 square degrees) simultaneous $^{12}$CO,\n$^{13}$CO, and C$^{18}$O ($J$=1$-$0) mapping of L1188 with the PMO 13.7-m\ntelescope. Our observations have revealed that L1188 consists of two nearly\northogonal filamentary molecular clouds at two clearly separated velocities.\nToward the intersection showing large velocity spreads, we find several\nbridging features connecting the two clouds in velocity, and an open arc\nstructure which exhibits high excitation temperatures, enhanced $^{12}$CO and\n$^{13}$CO emission, and broad $^{12}$CO line wings. This agrees with the\nscenario that the two clouds are colliding with each other. The distribution of\nyoung stellar object (YSO) candidates implies an enhancement of star formation\nin the intersection of the two clouds. We suggest that a cloud-cloud collision\nhappened in L1188 about 1~Myr ago, possibly triggering the formation of low-\nand intermediate-mass YSOs in the intersection.\n",
"title": "L1188: a promising candidate of cloud-cloud collision triggering the formation of the low- and intermediate-mass stars"
} | null | null | null | null | true | null | 18304 | null | Default | null | null |
null | {
"abstract": " Matrix-valued covariance functions are crucial to geostatistical modeling of\nmultivariate spatial data. The classical assumption of symmetry of a\nmultivariate covariance function is overlay restrictive and has been considered\nas unrealistic for most of real data applications. Despite of that, the\nliterature on asymmetric covariance functions has been very sparse. In\nparticular, there is some work related to asymmetric covariances on Euclidean\nspaces, depending on the Euclidean distance. However, for data collected over\nlarge portions of planet Earth, the most natural spatial domain is a sphere,\nwith the corresponding geodesic distance being the natural metric. In this\nwork, we propose a strategy based on spatial rotations to generate asymmetric\ncovariances for multivariate random fields on the $d$-dimensional unit sphere.\nWe illustrate through simulations as well as real data analysis that our\nproposal allows to achieve improvements in the predictive performance in\ncomparison to the symmetric counterpart.\n",
"title": "Asymmetric Matrix-Valued Covariances for Multivariate Random Fields on Spheres"
} | null | null | null | null | true | null | 18305 | null | Default | null | null |
null | {
"abstract": " We propose a new dynamic stochastic blockmodel that focuses on the analysis\nof interaction lengths in networks. The model does not rely on a discretization\nof the time dimension and may be used to analyze networks that evolve\ncontinuously over time. The framework relies on a clustering structure on the\nnodes, whereby two nodes belonging to the same latent group tend to create\ninteractions and non-interactions of similar lengths. We introduce a fast\nvariational expectation-maximization algorithm to perform inference, and adapt\na widely used clustering criterion to perform model choice. Finally, we test\nour methodology on artificial data, and propose a demonstration on a dataset\nconcerning face-to-face interactions between students in a high-school.\n",
"title": "A dynamic stochastic blockmodel for interaction lengths"
} | null | null | null | null | true | null | 18306 | null | Default | null | null |
null | {
"abstract": " Context: Visual aesthetics is increasingly seen as an essential factor in\nperceived usability, interaction, and overall appraisal of user interfaces\nespecially with respect to mobile applications. Yet, a question that remains is\nhow to assess and to which extend users agree on visual aesthetics. Objective:\nThis paper analyzes the inter-rater agreement on visual aesthetics of user\ninterfaces of Android apps as a basis for guidelines and evaluation models.\nMethod: We systematically collected ratings on the visual aesthetics of 100\nuser interfaces of Android apps from 10 participants and analyzed the frequency\ndistribution, reliability and influencing design aspects. Results: In general,\nuser interfaces of Android apps are perceived more ugly than beautiful. Yet,\nraters only moderately agree on the visual aesthetics. Disagreements seem to be\nrelated to subtle differences with respect to layout, shapes, colors,\ntypography, and background images. Conclusion: Visual aesthetics is a key\nfactor for the success of apps. However, the considerable disagreement of\nraters on the perceived visual aesthetics indicates the need for a better\nunderstanding of this software quality with respect to mobile apps.\n",
"title": "Do we agree on user interface aesthetics of Android apps?"
} | null | null | [
"Computer Science"
]
| null | true | null | 18307 | null | Validated | null | null |
null | {
"abstract": " A large-scale multi-object tracker based on the generalised labeled\nmulti-Bernoulli (GLMB) filter is proposed. The algorithm is capable of tracking\na very large, unknown and time-varying number of objects simultaneously, in the\npresence of a high number of false alarms, as well as misdetections and\nmeasurement origin uncertainty due to closely spaced objects. The algorithm is\ndemonstrated on a simulated large-scale tracking scenario, where the peak\nnumber objects appearing simultaneously exceeds one million. To evaluate the\nperformance of the proposed tracker, we also introduce a new method of applying\nthe optimal sub-pattern assignment (OSPA) metric, and an efficient strategy for\nits evaluation in large-scale scenarios.\n",
"title": "A Solution for Large-scale Multi-object Tracking"
} | null | null | null | null | true | null | 18308 | null | Default | null | null |
null | {
"abstract": " The coefficient of determination, known as $R^2$, is commonly used as a\ngoodness-of-fit criterion for fitting linear models. $R^2$ is somewhat\ncontroversial when fitting nonlinear models, although it may be generalised on\na case-by-case basis to deal with specific models such as the logistic model.\nAssume we are fitting a parametric distribution to a data set using, say, the\nmaximum likelihood estimation method. A general approach to measure the\ngoodness-of-fit of the fitted parameters, which we advocate herein, is to use a\nnonparametric measure for model comparison between the raw data and the fitted\nmodel. In particular, for this purpose we put forward the {\\em Survival\nJensen-Shannon divergence} ($SJS$) and its empirical counterpart (${\\cal\nE}SJS$) as a metric which is bounded, and is a natural generalisation of the\nJensen-Shannon divergence. We demonstrate, via a straightforward procedure\nmaking use of the ${\\cal E}SJS$, that it can be used as part of maximum\nlikelihood estimation or curve fitting as a measure of goodness-of-fit,\nincluding the construction of a confidence interval for the fitted parametric\ndistribution. Furthermore, we show the validity of the proposed method with\nsimulated data, and three empirical data sets of interest to researchers in\nsociophysics and econophysics.\n",
"title": "Empirical Survival Jensen-Shannon Divergence as a Goodness-of-Fit Measure for Maximum Likelihood Estimation and Curve Fitting"
} | null | null | null | null | true | null | 18309 | null | Default | null | null |
null | {
"abstract": " A GPS-denied UAV (Agent B) is localised through INS alignment with the aid of\na nearby GPS-equipped UAV (Agent A), which broadcasts its position at several\ntime instants. Agent B measures the signals' direction of arrival with respect\nto Agent B's inertial navigation frame. Semidefinite programming and the\nOrthogonal Procrustes algorithm are employed, and accuracy is improved through\nmaximum likelihood estimation. The method is validated using flight data and\nsimulations. A three-agent extension is explored.\n",
"title": "Cooperative Localisation of a GPS-Denied UAV using Direction of Arrival Measurements"
} | null | null | null | null | true | null | 18310 | null | Default | null | null |
null | {
"abstract": " The inner surface of superconducting cavities plays a crucial role to achieve\nhighest accelerating fields and low losses. The industrial fabrication of\ncavities for the European X-Ray Free Electron Laser (XFEL) and the\nInternational Linear Collider (ILC) HiGrade Research Project allowed for an\ninvestigation of this interplay. For the serial inspection of the inner\nsurface, the optical inspection robot OBACHT was constructed and to analyze the\nlarge amount of data, represented in the images of the inner surface, an image\nprocessing and analysis code was developed and new variables to describe the\ncavity surface were obtained. This quantitative analysis identified vendor\nspecific surface properties which allow to perform a quality control and\nassurance during the production. In addition, a strong negative correlation of\n$\\rho= -0.93$ with a significance of $6\\,\\sigma$ of the integrated grain\nboundary area $\\sum{\\mathrm{A}}$ versus the maximal achievable accelerating\nfield $\\mathrm{E_{acc,max}}$ has been found.\n",
"title": "Optical Surface Properties and their RF Limitations of European XFEL Cavities"
} | null | null | null | null | true | null | 18311 | null | Default | null | null |
null | {
"abstract": " In a recent paper by Lasseux, Valdés-Parada and Porter (J.~Fluid~Mech.\n\\textbf{805} (2016) 118-146), it is found that the apparent gas permeability of\nthe porous media is a nonlinear function of the Knudsen number. However, this\nresult is highly questionable, because the adopted Navier-Stokes equations and\nthe first-order velocity-slip boundary condition are first-order (in terms of\nthe Knudsen number) approximations of the Boltzmann equation and the kinetic\nboundary condition for rarefied gas flows. Our numerical simulations based on\nthe Bhatnagar-Gross-Krook kinetic equation and regularized 20-moment equations\nprove that the Navier-Stokes equations with the first-order velocity-slip\nboundary condition are only accurate at a very small Knudsen number limit,\nwhere the apparent gas permeability is a linear function of the Knudsen number.\n",
"title": "A comment on `An improved macroscale model for gas slip flow in porous media'"
} | null | null | [
"Physics"
]
| null | true | null | 18312 | null | Validated | null | null |
null | {
"abstract": " Highly distributed training of Deep Neural Networks (DNNs) on future compute\nplatforms (offering 100 of TeraOps/s of computational capacity) is expected to\nbe severely communication constrained. To overcome this limitation, new\ngradient compression techniques are needed that are computationally friendly,\napplicable to a wide variety of layers seen in Deep Neural Networks and\nadaptable to variations in network architectures as well as their\nhyper-parameters. In this paper we introduce a novel technique - the Adaptive\nResidual Gradient Compression (AdaComp) scheme. AdaComp is based on localized\nselection of gradient residues and automatically tunes the compression rate\ndepending on local activity. We show excellent results on a wide spectrum of\nstate of the art Deep Learning models in multiple domains (vision, speech,\nlanguage), datasets (MNIST, CIFAR10, ImageNet, BN50, Shakespeare), optimizers\n(SGD with momentum, Adam) and network parameters (number of learners,\nminibatch-size etc.). Exploiting both sparsity and quantization, we demonstrate\nend-to-end compression rates of ~200X for fully-connected and recurrent layers,\nand ~40X for convolutional layers, without any noticeable degradation in model\naccuracies.\n",
"title": "AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training"
} | null | null | null | null | true | null | 18313 | null | Default | null | null |
null | {
"abstract": " We present a halo-independent determination of the unmodulated signal\ncorresponding to the DAMA modulation if interpreted as due to dark matter\nweakly interacting massive particles (WIMPs). First we show how a modulated\nsignal gives information on the WIMP velocity distribution function in the\nGalactic rest frame, from which the unmodulated signal descends. Then we\nperform a mathematically-sound profile likelihood analysis in which we profile\nthe likelihood over a continuum of nuisance parameters (namely, the WIMP\nvelocity distribution). As a first application of the method, which is very\ngeneral and valid for any class of velocity distributions, we restrict the\nanalysis to velocity distributions that are isotropic in the Galactic frame. In\nthis way we obtain halo-independent maximum-likelihood estimates and confidence\nintervals for the DAMA unmodulated signal. We find that the estimated\nunmodulated signal is in line with expectations for a WIMP-induced modulation\nand is compatible with the DAMA background+signal rate. Specifically, for the\nisotropic case we find that the modulated amplitude ranges between a few\npercent and about 25% of the unmodulated amplitude, depending on the WIMP mass.\n",
"title": "Halo-independent determination of the unmodulated WIMP signal in DAMA: the isotropic case"
} | null | null | null | null | true | null | 18314 | null | Default | null | null |
null | {
"abstract": " Deep reinforcement learning has achieved many recent successes, but our\nunderstanding of its strengths and limitations is hampered by the lack of rich\nenvironments in which we can fully characterize optimal behavior, and\ncorrespondingly diagnose individual actions against such a characterization.\nHere we consider a family of combinatorial games, arising from work of Erdos,\nSelfridge, and Spencer, and we propose their use as environments for evaluating\nand comparing different approaches to reinforcement learning. These games have\na number of appealing features: they are challenging for current learning\napproaches, but they form (i) a low-dimensional, simply parametrized\nenvironment where (ii) there is a linear closed form solution for optimal\nbehavior from any state, and (iii) the difficulty of the game can be tuned by\nchanging environment parameters in an interpretable way. We use these\nErdos-Selfridge-Spencer games not only to compare different algorithms, but\ntest for generalization, make comparisons to supervised learning, analyse\nmultiagent play, and even develop a self play algorithm. Code can be found at:\nthis https URL\n",
"title": "Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?"
} | null | null | null | null | true | null | 18315 | null | Default | null | null |
null | {
"abstract": " In his seminal paper, Chua presented a fundamental physical claim by\nintroducing the memristor, \"The missing circuit element\". The memristor\nequations were originally supposed to represent a passive circuit element\nbecause, with active circuitry, arbitrary elements can be realized without\nlimitations. Therefore, if the memristor equations do not guarantee that the\ncircuit element can be realized by a passive system, the fundamental physics\nclaim about the memristor as \"missing circuit element\" loses all its weight.\nThe question of passivity/activity belongs to physics thus we incorporate\nthermodynamics into the study of this problem. We show that the memristor\nequations are physically incomplete regarding the problem of\npassivity/activity. As a consequence, the claim that the present memristor\nfunctions describe a passive device lead to unphysical results, such as\nviolating the Second Law of thermodynamics, in infinitely large number of\ncases. The seminal memristor equations cannot introduce a new physical circuit\nelement without making the model more physical such as providing the\nFluctuation Dissipation Theory of memristors.\n",
"title": "Memristor equations: incomplete physics and undefined passivity/activity"
} | null | null | null | null | true | null | 18316 | null | Default | null | null |
null | {
"abstract": " The differential event rate in Weakly Interacting Massive Particle (WIMP)\ndirect detection experiments depends on the local dark matter density and\nvelocity distribution. Accurate modelling of the local dark matter distribution\nis therefore required to obtain reliable constraints on the WIMP particle\nphysics properties. Data analyses typically use a simple Standard Halo Model\nwhich might not be a good approximation to the real Milky Way (MW) halo. We\nreview observational determinations of the local dark matter density, circular\nspeed and escape speed and also studies of the local dark matter distribution\nin simulated MW-like galaxies. We discuss the effects of the uncertainties in\nthese quantities on the energy spectrum and its time and direction dependence.\nFinally we conclude with an overview of various methods for handling these\nastrophysical uncertainties.\n",
"title": "Astrophysical uncertainties on the local dark matter distribution and direct detection experiments"
} | null | null | null | null | true | null | 18317 | null | Default | null | null |
null | {
"abstract": " In the past few years, datacenter (DC) energy consumption has become an\nimportant issue in technology world. Server consolidation using virtualization\nand virtual machine (VM) live migration allows cloud DCs to improve resource\nutilization and hence energy efficiency. In order to save energy, consolidation\ntechniques try to turn off the idle servers, while because of workload\nfluctuations, these offline servers should be turned on to support the\nincreased resource demands. These repeated on-off cycles could affect the\nhardware reliability and wear-and-tear of servers and as a result, increase the\nmaintenance and replacement costs. In this paper we propose a holistic\nmathematical model for reliability-aware server consolidation with the\nobjective of minimizing total DC costs including energy and reliability costs.\nIn fact, we try to minimize the number of active PMs and racks, in a\nreliability-aware manner. We formulate the problem as a Mixed Integer Linear\nProgramming (MILP) model which is in form of NP-complete. Finally, we evaluate\nthe performance of our approach in different scenarios using extensive\nnumerical MATLAB simulations.\n",
"title": "On Reliability-Aware Server Consolidation in Cloud Datacenters"
} | null | null | null | null | true | null | 18318 | null | Default | null | null |
null | {
"abstract": " The numerical analysis of the diffraction features rendered by transmission\nelectron microscopy (TEM) typically relies either on classical approximations\n(Monte Carlo simulations) or quantum paraxial tomography (the multislice method\nand any of its variants). Although numerically advan- tageous (relatively\nsimple implementations and low computational costs), they involve important\napproximations and thus their range of applicability is limited. To overcome\nsuch limitations, an alternative, more general approach is proposed, based on\nan optimal combination of wave-packet propagation with the on-the-fly\ncomputation of associated Bohmian trajectories. For the sake of clarity, but\nwithout loss of generality, the approach is used to analyze the diffraction of\nan electron beam by a thin aluminum slab as a function of three different\nincidence (work) conditions which are of interest in electron microscopy: the\nprobe width, the tilting angle, and the beam energy. Specifically, it is shown\nthat, because there is a dependence on particular thresholds of the beam\nenergy, this approach provides a clear description of the diffraction process\nat any energy, revealing at the same time any diversion of the beam inside the\nmaterial towards directions that cannot be accounted for by other conventional\nmethods, which is of much interest when dealing with relatively low energies\nand/or relatively large tilting angles.\n",
"title": "A novel quantum dynamical approach in electron microscopy combining wave-packet propagation with Bohmian trajectories"
} | null | null | null | null | true | null | 18319 | null | Default | null | null |
null | {
"abstract": " We show that any $d$-colored set of points in general position in\n$\\mathbb{R}^d$ can be partitioned into $n$ subsets with disjoint convex hulls\nsuch that the set of points and all color classes are partitioned as evenly as\npossible. This extends results by Holmsen, Kynčl & Valculescu (2017) and\nestablishes a special case of their general conjecture. Our proof utilizes a\nresult obtained independently by Soberón and by Karasev in 2010, on\nsimultaneous equipartitions of $d$ continuous measures in $\\mathbb{R}^d$ by $n$\nconvex regions. This gives a convex partition of $\\mathbb{R}^d$ with the\ndesired properties, except that points may lie on the boundaries of the\nregions. In order to resolve the ambiguous assignment of these points, we set\nup a network flow problem. The equipartition of the continuous measures gives a\nfractional flow. The existence of an integer flow then yields the desired\npartition of the point set.\n",
"title": "Convex equipartitions of colored point sets"
} | null | null | null | null | true | null | 18320 | null | Default | null | null |
null | {
"abstract": " With the purpose of modeling, specifying and reasoning in an integrated\nfashion with procedural and declarative aspects (both commonly present in cases\nor scenarios), the paper introduces Logic Programming Petri Nets (LPPN), an\nextension to the Petri Net notation providing an interface to logic programming\nconstructs. Two semantics are presented. First, a hybrid operational semantics\nthat separates the process component, treated with Petri nets, from the\nconstraint/terminological component, treated with Answer Set Programming (ASP).\nSecond, a denotational semantics maps the notation to ASP fully, via Event\nCalculus. These two alternative specifications enable a preliminary evaluation\nin terms of reasoning efficiency.\n",
"title": "Logic Programming Petri Nets"
} | null | null | null | null | true | null | 18321 | null | Default | null | null |
null | {
"abstract": " We consider higher order parabolic operator $\\partial_t+(-\\Delta_x)^m$ and\nhigher order Schrödinger operator $i^{-1}\\partial_t+(-\\Delta_x)^m$ in\n$X=\\{(t,x)\\in\\mathbb{R}^{1+n};~|t|<A,|x_n|<B\\}$ where $m$ is any positive\ninteger. Under certain lower order and regularity assumptions, we prove that if\nthe solution for linear problem vanishes when $x_n>0$, then the solution\nvanishes in $X$. Such results are given globally, and we also prove some\nrelated local results.\n",
"title": "Unique Continuation through Hyperplane for Higher Order Parabolic and Shrödinger Equations"
} | null | null | null | null | true | null | 18322 | null | Default | null | null |
null | {
"abstract": " The fashion industry is establishing its presence on a number of\nvisual-centric social media like Instagram. This creates an interesting clash\nas fashion brands that have traditionally practiced highly creative and\neditorialized image marketing now have to engage with people on the platform\nthat epitomizes impromptu, realtime conversation. What kinds of fashion images\ndo brands and individuals share and what are the types of visual features that\nattract likes and comments? In this research, we take both quantitative and\nqualitative approaches to answer these questions. We analyze visual features of\nfashion posts first via manual tagging and then via training on convolutional\nneural networks. The classified images were examined across four types of\nfashion brands: mega couture, small couture, designers, and high street. We\nfind that while product-only images make up the majority of fashion\nconversation in terms of volume, body snaps and face images that portray\nfashion items more naturally tend to receive a larger number of likes and\ncomments by the audience. Our findings bring insights into building an\nautomated tool for classifying or generating influential fashion information.\nWe make our novel dataset of {24,752} labeled images on fashion conversations,\ncontaining visual and textual cues, available for the research community.\n",
"title": "Fashion Conversation Data on Instagram"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 18323 | null | Validated | null | null |
null | {
"abstract": " Fluid-structure interactions are ubiquitous in nature and technology.\nHowever, the systems are often so complex that numerical simulations or ad hoc\nassumptions must be used to gain insight into the details of the complex\ninteractions between the fluid and solid mechanics. In this paper, we present\nexperiments and theory on viscous flow in a simple bioinspired soft valve which\nillustrate essential features of interactions between hydrodynamic and elastic\nforces at low Reynolds numbers. The setup comprises a sphere connected to a\nspring located inside a tapering cylindrical channel. The spring is aligned\nwith the central axis of the channel and a pressure drop is applied across the\nsphere, thus forcing the liquid through the narrow gap between the sphere and\nthe channel walls. The sphere's equilibrium position is determined by a balance\nbetween spring and hydrodynamic forces. Since the gap thickness changes with\nthe sphere's position, the system has a pressure-dependent hydraulic\nresistance. This leads to a non-linear relation between applied pressure and\nflow rate: flow initially increases with pressure, but decreases when the\npressure exceeds a certain critical value as the gap closes. To rationalize\nthese observations, we propose a mathematical model that reduced the complexity\nof the flow to a two-dimensional lubrication approximation. A closed-form\nexpression for the pressure-drop/flow rate is obtained which reveals that the\nflow rate $Q$ depends on the pressure drop $\\Delta p$, sphere radius $a$, gap\nthickness $h_0$, and viscosity $\\eta$ as $Q\\sim \\eta^{-1}\na^{1/2}h_0^{5/2}\\left(\\Delta p_c-\\Delta p\\right)^{5/2}\\Delta p$, where the\ncritical pressure $\\Delta p_c$ scales with the spring constant $k$ and sphere\nradius $a$ as $\\Delta p_c\\sim k a^{-2}$. These predictions compared favorably\nto the results of our experiments with no free parameters.\n",
"title": "Viscous flow in a soft valve"
} | null | null | null | null | true | null | 18324 | null | Default | null | null |
null | {
"abstract": " The early universe could feature multiple reheating events, leading to jumps\nin the visible sector entropy density that dilute both particle asymmetries and\nthe number density of frozen-out states. In fact, late time entropy jumps are\nusually required in models of Affleck-Dine baryogenesis, which typically\nproduces an initial particle-antiparticle asymmetry that is much too large. An\nimportant consequence of late time dilution, is that a smaller dark matter\nannihilation cross section is needed to obtain the observed dark matter relic\ndensity. For cosmologies with high scale baryogenesis, followed by\nradiation-dominated dark matter freeze-out, we show that the perturbative\nunitarity mass bound on thermal relic dark matter is relaxed to $10^{10}$ GeV.\nWe proceed to study superheavy asymmetric dark matter models, made possible by\na sizable entropy injection after dark matter freeze-out, and identify how the\nAffleck-Dine mechanism would generate the baryon and dark asymmetries.\n",
"title": "Superheavy Thermal Dark Matter and Primordial Asymmetries"
} | null | null | [
"Physics"
]
| null | true | null | 18325 | null | Validated | null | null |
null | {
"abstract": " We propose an intuitive method, called time-dependent population imaging\n(TDPI), to map the dynamical processes of high harmonic generation (HHG) in\nsolids by solving the time-dependent Schrödinger equation (TDSE). It is\nshown that the real-time dynamical characteristics of HHG in solids, such as\nthe instantaneous photon energies of emitted harmonics, can be read directly\nfrom the energy-resolved population oscillations of electrons in the TDPIs.\nMeanwhile, the short and long trajectories of solid HHG are illustrated clearly\nfrom TDPI. By using the TDPI, we also investigate the effects of\ncarrier-envelope phase (CEP) in few-cycle pulses and intuitively demonstrate\nthe HHG dynamics driven by two-color fields. Our results show that the TDPI\nprovides a powerful tool to study the ultrafast dynamics in strong fields for\nvarious laser-solid configurations and gain an insight into HHG processes in\nsolids.\n",
"title": "Time-dependent population imaging for solid high harmonic generation"
} | null | null | null | null | true | null | 18326 | null | Default | null | null |
null | {
"abstract": " Predicting epidemic dynamics is of great value in understanding and\ncontrolling diffusion processes, such as infectious disease spread and\ninformation propagation. This task is intractable, especially when surveillance\nresources are very limited. To address the challenge, we study the problem of\nactive surveillance, i.e., how to identify a small portion of system components\nas sentinels to effect monitoring, such that the epidemic dynamics of an entire\nsystem can be readily predicted from the partial data collected by such\nsentinels. We propose a novel measure, the gamma value, to identify the\nsentinels by modeling a sentinel network with row sparsity structure. We design\na flexible group sparse Bayesian learning algorithm to mine the sentinel\nnetwork suitable for handling both linear and non-linear dynamical systems by\nusing the expectation maximization method and variational approximation. The\nefficacy of the proposed algorithm is theoretically analyzed and empirically\nvalidated using both synthetic and real-world data.\n",
"title": "Group Sparse Bayesian Learning for Active Surveillance on Epidemic Dynamics"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 18327 | null | Validated | null | null |
null | {
"abstract": " Limitations in processing capabilities and memory of today's computers make\nspiking neuron-based (human) whole-brain simulations inevitably characterized\nby a compromise between bio-plausibility and computational cost. It translates\ninto brain models composed of a reduced number of neurons and a simplified\nneuron's mathematical model. Taking advantage of the sparse character of\nbrain-like computation, eventdriven technique allows us to carry out efficient\nsimulation of large-scale Spiking Neural Networks (SNN). The recent Leaky\nIntegrate-and-Fire with Latency (LIFL) spiking neuron model is event-driven\ncompatible and exhibits some realistic neuronal features, opening new horizons\nin whole-brain modelling. In this paper we present FNS, a LIFL-based exact\nevent-driven spiking neural network framework implemented in Java and oriented\nto wholebrain simulations. FNS combines spiking/synaptic whole-brain modelling\nwith the event-driven approach, allowing us to define heterogeneous modules and\nmulti-scale connectivity with delayed connections and plastic synapses,\nproviding fast simulations at the same time. A novel parallelization strategy\nis also implemented in order to further speed up simulations. This paper\npresents mathematical models, software implementation and simulation routines\non which FNS is based. Finally, a reduced brain network model (1400 neurons and\n45000 synapses) is synthesized on the basis of real brain structural data, and\nthe resulting model activity is compared with associated brain functional\n(source-space MEG) data. The conducted test shows a good matching between the\nactivity of model and that of the emulated subject, in outstanding simulation\ntimes (about 20s for simulating 4s of activity with a normal PC). Dedicated\nsections of stimuli editing and output synthesis allow the neuroscientist to\nintroduce and extract brain-like signals, respectively...\n",
"title": "FNS: an event-driven spiking neural network framework for efficient simulations of large-scale brain models"
} | null | null | null | null | true | null | 18328 | null | Default | null | null |
null | {
"abstract": " The problem of synchronization of coupled Hamiltonian systems exhibits\ninteresting features due to the non-uniform or mixed nature (regular and\nchaotic) of the phase space. We study these features by investigating the\nsynchronization of unidirectionally coupled area-preserving maps coupled by the\nPecora-Carroll method. We find that coupled standard maps show complete\nsynchronization for values of the nonlinearity parameter at which regular\nstructures are still present in phase space. The distribution of\nsynchronization times has a power law tail indicating long synchronization\ntimes for at least some of the synchronizing trajectories. With the\nintroduction of coherent structures using parameter perturbation in the system,\nthis distribution crosses over to exponential behavior, indicating shorter\nsynchronization times, and the number of initial conditions which synchronize\nincreases significantly, indicating an enhancement in the basin of\nsynchronization. On the other hand, coupled blinking vortex maps display both\nphase synchronization and phase slips, depending on the location of the initial\nconditions. We discuss the implication of our results.\n",
"title": "Synchronization, phase slips and coherent structures in area-preserving maps"
} | null | null | null | null | true | null | 18329 | null | Default | null | null |
null | {
"abstract": " Semantic segmentation remains a computationally intensive algorithm for\nembedded deployment even with the rapid growth of computation power. Thus\nefficient network design is a critical aspect especially for applications like\nautomated driving which requires real-time performance. Recently, there has\nbeen a lot of research on designing efficient encoders that are mostly task\nagnostic. Unlike image classification and bounding box object detection tasks,\ndecoders are computationally expensive as well for semantic segmentation task.\nIn this work, we focus on efficient design of the segmentation decoder and\nassume that an efficient encoder is already designed to provide shared features\nfor a multi-task learning system. We design a novel efficient non-bottleneck\nlayer and a family of decoders which fit into a small run-time budget using\nVGG10 as efficient encoder. We demonstrate in our dataset that experimentation\nwith various design choices led to an improvement of 10\\% from a baseline\nperformance.\n",
"title": "Design of Real-time Semantic Segmentation Decoder for Automated Driving"
} | null | null | null | null | true | null | 18330 | null | Default | null | null |
null | {
"abstract": " Motivated by applications of mixed longitudinal studies, where a group of\nsubjects entering the study at different ages (cross-sectional) are followed\nfor successive years (longitudinal), we consider nonparametric covariance\nestimation with samples of noisy and partially-observed functional\ntrajectories. To ensure model identifiability and estimation consistency, we\nintroduce and carefully discuss the reduced rank and neighboring incoherence\ncondition. The proposed algorithm is based on a sequential-aggregation scheme,\nwhich is non-iterative, with only basic matrix operations and closed-form\nsolutions in each step. The good performance of the proposed method is\nsupported by both theory and numerical experiments. We also apply the proposed\nprocedure to a midlife women's working memory study based on the data from the\nStudy of Women's Health Across the Nation (SWAN).\n",
"title": "Nonparametric covariance estimation for mixed longitudinal studies, with applications in midlife women's health"
} | null | null | [
"Mathematics",
"Statistics"
]
| null | true | null | 18331 | null | Validated | null | null |
null | {
"abstract": " The recent Nobel-prize-winning detections of gravitational waves from merging\nblack holes and the subsequent detection of the collision of two neutron stars\nin coincidence with electromagnetic observations have inaugurated a new era of\nmultimessenger astrophysics. To enhance the scope of this emergent science, we\nproposed the use of deep convolutional neural networks for the detection and\ncharacterization of gravitational wave signals in real-time. This method, Deep\nFiltering, was initially demonstrated using simulated LIGO noise. In this\narticle, we present the extension of Deep Filtering using real data from the\nfirst observing run of LIGO, for both detection and parameter estimation of\ngravitational waves from binary black hole mergers with continuous data streams\nfrom multiple LIGO detectors. We show for the first time that machine learning\ncan detect and estimate the true parameters of a real GW event observed by\nLIGO. Our comparisons show that Deep Filtering is far more computationally\nefficient than matched-filtering, while retaining similar sensitivity and lower\nerrors, allowing real-time processing of weak time-series signals in\nnon-stationary non-Gaussian noise, with minimal resources, and also enables the\ndetection of new classes of gravitational wave sources that may go unnoticed\nwith existing detection algorithms. This approach is uniquely suited to enable\ncoincident detection campaigns of gravitational waves and their multimessenger\ncounterparts in real-time.\n",
"title": "Deep Learning for Real-time Gravitational Wave Detection and Parameter Estimation with LIGO Data"
} | null | null | null | null | true | null | 18332 | null | Default | null | null |
null | {
"abstract": " I outline a construction of a local Floer homology for a coisotropic\nsubmanifold of a symplectic manifold and explain how it can be used to show\nthat leafwise fixed points of Hamiltonian diffeomorphisms exist.\n",
"title": "Note on local coisotropic Floer homology and leafwise fixed points"
} | null | null | null | null | true | null | 18333 | null | Default | null | null |
null | {
"abstract": " This paper presents contributions on nonlinear tracking control systems for a\nquadrotor unmanned micro aerial vehicle. New controllers are proposed based on\nnonlinear surfaces composed by tracking errors that evolve directly on the\nnonlinear configuration manifold thus inherently including in the control\ndesign the nonlinear characteristics of the SE(3) configuration space. In\nparticular geometric surface-based controllers are developed, and through\nrigorous stability proofs they are shown to have desirable closed loop\nproperties that are almost global. A region of attraction, independent of the\nposition error, is produced and its effects are analyzed. A strategy allowing\nthe quadrotor to achieve precise attitude tracking while simultaneously\nfollowing a desired position command and complying to actuator constraints in a\ncomputationally inexpensive manner is derived. This important contribution\ndifferentiates this work from existing Geometric Nonlinear Control System\nsolutions (GNCSs) since the commanded thrusts can be realized by the majority\nof quadrotors produced by the industry. The new features of the proposed GNCSs\nare illustrated by numerical simulations of aggressive maneuvers and a\ncomparison with a GNCSs from the bibliography.\n",
"title": "Geometric Surface-Based Tracking Control of a Quadrotor UAV under Actuator Constraints"
} | null | null | null | null | true | null | 18334 | null | Default | null | null |
null | {
"abstract": " We consider the problem of estimating the the rate of defects (mean number of\ndefects per item), given counts of defects detected by two independent\nimperfect inspectors on a sample of items. In contrast with the well-known\nmethod of Capture-Recapture, here we {\\it{do not}} have information regarding\nthe number of defects jointly detected by {\\it{both}} inspectors. We solve this\nproblem by constructing two types of estimators - a simple moment-type\nestimator, and a more complicated maximum-likelihood estimator. The performance\nof these estimators is studied analytically and by means of simulations. It is\nshown that the maximum-likelihood estimator is superior to the moment-type\nestimator. A systematic comparison with the Capture-Recapture method is also\nmade.\n",
"title": "Estimating the rate of defects under imperfect sampling inspection - a new approach"
} | null | null | null | null | true | null | 18335 | null | Default | null | null |
null | {
"abstract": " Different questions related with analysis of extreme values and outliers\narise frequently in practice. To exclude extremal observations and outliers is\nnot a good decision because they contain important information about the\nobserved distribution. The difficulties with their usage are usually related to\nthe estimation of the tail index in case it exists. There are many measures for\nthe center of the distribution, e.g. mean, mode, median. There are many\nmeasures of the variance, asymmetry, and kurtosis, but there is no easy\ncharacteristic for heavy-tailedness of the observed distribution. Here we\npropose such a measure, give some examples and explore some of its properties.\nThis allows us to introduce a classification of the distributions, with respect\nto their heavy-tailedness. The idea is to help and navigate practitioners for\naccurate and easier work in the field of probability distributions.\nUsing the properties of the defined characteristics some distribution\nsensitive extremal index estimators are proposed and their properties are\npartially investigated.\n",
"title": "Measuring heavy-tailedness of distributions"
} | null | null | null | null | true | null | 18336 | null | Default | null | null |
null | {
"abstract": " Inductive $k$-independent graphs generalize chordal graphs and have recently\nbeen advocated in the context of interference-avoiding wireless communication\nscheduling. The NP-hard problem of finding maximum-weight induced $c$-colorable\nsubgraphs, which is a generalization of finding maximum independent sets,\nnaturally occurs when selecting $c$ sets of pairwise non-conflicting jobs\n(modeled as graph vertices). We investigate the parameterized complexity of\nthis problem on inductive $k$-independent graphs. We show that the Independent\nSet problem is W[1]-hard even on 2-simplicial 3-minoes---a subclass of\ninductive 2-independent graphs. In contrast, we prove that the more general\nMaximum $c$-Colorable Subgraph problem is fixed-parameter tractable on\nedge-wise unions of cluster and chordal graphs, which are 2-simplicial. In both\ncases, the parameter is the solution size. Aside from this, we survey other\ngraph classes between inductive 1-inductive and inductive 2-inductive graphs\nwith applications in scheduling.\n",
"title": "Inductive $k$-independent graphs and $c$-colorable subgraphs in scheduling: A review"
} | null | null | null | null | true | null | 18337 | null | Default | null | null |
null | {
"abstract": " We prove that the word problem is undecidable in functionally recursive\ngroups, and that the order problem is undecidable in automata groups, even\nunder the assumption that they are contracting.\n",
"title": "The word and order problems for self-similar and automata groups"
} | null | null | null | null | true | null | 18338 | null | Default | null | null |
null | {
"abstract": " The current processes for building machine learning systems require\npractitioners with deep knowledge of machine learning. This significantly\nlimits the number of machine learning systems that can be created and has led\nto a mismatch between the demand for machine learning systems and the ability\nfor organizations to build them. We believe that in order to meet this growing\ndemand for machine learning systems we must significantly increase the number\nof individuals that can teach machines. We postulate that we can achieve this\ngoal by making the process of teaching machines easy, fast and above all,\nuniversally accessible.\nWhile machine learning focuses on creating new algorithms and improving the\naccuracy of \"learners\", the machine teaching discipline focuses on the efficacy\nof the \"teachers\". Machine teaching as a discipline is a paradigm shift that\nfollows and extends principles of software engineering and programming\nlanguages. We put a strong emphasis on the teacher and the teacher's\ninteraction with data, as well as crucial components such as techniques and\ndesign principles of interaction and visualization.\nIn this paper, we present our position regarding the discipline of machine\nteaching and articulate fundamental machine teaching principles. We also\ndescribe how, by decoupling knowledge about machine learning algorithms from\nthe process of teaching, we can accelerate innovation and empower millions of\nnew uses for machine learning models.\n",
"title": "Machine Teaching: A New Paradigm for Building Machine Learning Systems"
} | null | null | null | null | true | null | 18339 | null | Default | null | null |
null | {
"abstract": " We show that any totally geodesic submanifold of Teichmuller space of\ndimension greater than one covers a totally geodesic subvariety, and only\nfinitely many totally geodesic subvarieties of dimension greater than one exist\nin each moduli space.\n",
"title": "Totally geodesic submanifolds of Teichmuller space"
} | null | null | null | null | true | null | 18340 | null | Default | null | null |
null | {
"abstract": " We show that $K(2)$-locally, the smash product of the string bordism spectrum\nand the spectrum $T_2$ splits into copies of Morava $E$-theories. Here, $T_2$\nis related to the Thom spectrum of the canonical bundle over $\\Omega SU(4)$.\n",
"title": "Towards a splitting of the $K(2)$-local string bordism spectrum"
} | null | null | [
"Mathematics"
]
| null | true | null | 18341 | null | Validated | null | null |
null | {
"abstract": " In this paper, we explore various forms of osmotic transport in the regime of\nhigh solute concentration. We consider both the osmosis across membranes and\ndiffusio-osmosis at solid interfaces, driven by solute concentration gradients.\nWe follow a mechanical point of view of osmotic transport, which allows us to\ngain much insight into the local mechanical balance underlying osmosis. We\ndemonstrate in particular how the general expression of the osmotic pressure\nfor mixtures, as obtained classically from the thermodynamic framework, emerges\nfrom the mechanical balance controlling non-equilibrium transport under solute\ngradients. Expressions for the rejection coefficient of osmosis and the\ndiffusio-osmotic mobilities are accordingly obtained. These results generalize\nexisting ones in the dilute solute regime to mixtures with arbitrary\nconcentrations.\n",
"title": "Osmotic and diffusio-osmotic flow generation at high solute concentration. I. Mechanical approaches"
} | null | null | null | null | true | null | 18342 | null | Default | null | null |
null | {
"abstract": " Small $p$-values are often required to be accurately estimated in large scale\ngenomic studies for the adjustment of multiple hypothesis tests and the ranking\nof genomic features based on their statistical significance. For those\ncomplicated test statistics whose cumulative distribution functions are\nanalytically intractable, existing methods usually do not work well with small\n$p$-values due to lack of accuracy or computational restrictions. We propose a\ngeneral approach for accurately and efficiently calculating small $p$-values\nfor a broad range of complicated test statistics based on the principle of the\ncross-entropy method and Markov chain Monte Carlo sampling techniques. We\nevaluate the performance of the proposed algorithm through simulations and\ndemonstrate its application to three real examples in genomic studies. The\nresults show that our approach can accurately evaluate small to extremely small\n$p$-values (e.g. $10^{-6}$ to $10^{-100}$). The proposed algorithm is helpful\nto the improvement of existing test procedures and the development of new test\nprocedures in genomic studies.\n",
"title": "Accurate and Efficient Estimation of Small P-values with the Cross-Entropy Method: Applications in Genomic Data Analysis"
} | null | null | null | null | true | null | 18343 | null | Default | null | null |
null | {
"abstract": " Researchers have previously shown that Coincidental Correctness (CC) is\nprevalent; however, the benchmarks they used are considered inadequate\nnowadays. They have also recognized the negative impact of CC on the\neffectiveness of fault localization and testing. The aim of this paper is to\nstudy Coincidental Correctness, using more realistic code, mainly from the\nperspective of unit testing. This stems from the fact that the practice of unit\ntesting has grown tremendously in recent years due to the wide adoption of\nsoftware development processes, such as Test-Driven Development. We quantified\nthe presence of CC in unit testing using the Defects4J benchmark. This entailed\nmanually injecting two code checkers for each of the 395 defects in Defects4J:\n1) a weak checker that detects weak CC tests by monitoring whether the defect\nwas reached; and 2) a strong checker that detects strong CC tests by monitoring\nwhether the defect was reached and the program has transitioned into an\ninfectious state. We also conducted preliminary experiments (using Defects4J,\nNanoXML and JTidy) to assess the pervasiveness of CC at the unit testing level\nin comparison to that at the integration and system levels. Our study showed\nthat unit testing is not immune to CC, as it exhibited 7.2x more strong CC\ntests than failing tests and 8.3x more weak CC tests than failing tests.\nHowever, our preliminary results suggested that it might be less prone to CC\nthan integration testing and system testing.\n",
"title": "Does the Testing Level affect the Prevalence of Coincidental Correctness?"
} | null | null | null | null | true | null | 18344 | null | Default | null | null |
null | {
"abstract": " We observe the effects of the three different events that cause spread\nchanges in the order book, namely trades, deletions and placement of limit\norders. By looking at the frequencies of the relative amounts of price changing\nevents, we discover that deletions of orders open the bid-ask spread of a stock\nmore often than trades do. We see that once the amount of spread changes due to\ndeletions exceeds the amount of the ones due to trades, other observables in\nthe order book change as well. We then look at how these spread changing events\naffect the prices of stocks, by means of the price response. We not only see\nthat the self-response of stocks is positive for both spread changing trades\nand deletions and negative for order placements, but also cross-response to\nother stocks and therefore the market as a whole. In addition, the\nself-response function of spread-changing trades is similar to that of all\ntrades. This leads to the conclusion that spread changing deletions and order\nplacements have a similar effect on the order book and stock prices over time\nas trades.\n",
"title": "How spread changes affect the order book: Comparing the price responses of order deletions and placements to trades"
} | null | null | null | null | true | null | 18345 | null | Default | null | null |
null | {
"abstract": " In this paper, we consider the use of structure learning methods for\nprobabilistic graphical models to identify statistical dependencies in\nhigh-dimensional physical processes. Such processes are often synthetically\ncharacterized using PDEs (partial differential equations) and are observed in a\nvariety of natural phenomena, including geoscience data capturing atmospheric\nand hydrological phenomena. Classical structure learning approaches such as the\nPC algorithm and variants are challenging to apply due to their high\ncomputational and sample requirements. Modern approaches, often based on sparse\nregression and variants, do come with finite sample guarantees, but are usually\nhighly sensitive to the choice of hyper-parameters, e.g., parameter $\\lambda$\nfor sparsity inducing constraint or regularization. In this paper, we present\nACLIME-ADMM, an efficient two-step algorithm for adaptive structure learning,\nwhich estimates an edge specific parameter $\\lambda_{ij}$ in the first step,\nand uses these parameters to learn the structure in the second step. Both steps\nof our algorithm use (inexact) ADMM to solve suitable linear programs, and all\niterations can be done in closed form in an efficient block parallel manner. We\ncompare ACLIME-ADMM with baselines on both synthetic data simulated by partial\ndifferential equations (PDEs) that model advection-diffusion processes, and\nreal data (50 years) of daily global geopotential heights to study information\nflow in the atmosphere. ACLIME-ADMM is shown to be efficient, stable, and\ncompetitive, usually better than the baselines especially on difficult\nproblems. On real data, ACLIME-ADMM recovers the underlying structure of global\natmospheric circulation, including switches in wind directions at the equator\nand tropics entirely from the data.\n",
"title": "High-Dimensional Dependency Structure Learning for Physical Processes"
} | null | null | null | null | true | null | 18346 | null | Default | null | null |
null | {
"abstract": " We show that, for a quantale $V$ and a $\\mathsf{Set}$-monad $\\mathbb{T}$\nlaxly extended to $V$-$\\mathsf{Rel}$, the presheaf monad on the category of\n$(\\mathbb{T},V)$-categories is simple, giving rise to a lax orthogonal\nfactorisation system (lofs) whose corresponding weak factorisation system has\nembeddings as left part. In addition, we present presheaf submonads and study\nthe LOFSs they define. This provides a method of constructing weak\nfactorisation systems on some well-known examples of topological categories\nover $\\mathsf{Set}$.\n",
"title": "Lax orthogonal factorisations in monad-quantale-enriched categories"
} | null | null | null | null | true | null | 18347 | null | Default | null | null |
null | {
"abstract": " We compute the leading Post-Newtonian (PN) contributions at linear order in\nthe spin to the radiation-reaction acceleration and spin evolution for binary\nsystems, which enter at fourth PN order. The calculation is carried out, from\nfirst principles, using the effective field theory framework for spinning\ncompact objects, in both the Newton-Wigner and covariant spin supplementary\nconditions. A non-trivial consistency check is performed on our results by\nshowing that the energy loss induced by the resulting radiation-reaction force\nis equivalent to the total emitted power in the far zone, up to so-called\n\"Schott terms.\" We also find that, at this order, the radiation reaction has no\nnet effect on the evolution of the spins. The spin-spin contributions to\nradiation reaction are reported in a companion paper.\n",
"title": "Radiation reaction for spinning bodies in effective field theory I: Spin-orbit effects"
} | null | null | null | null | true | null | 18348 | null | Default | null | null |
null | {
"abstract": " Tangent categories provide an axiomatic approach to key structural aspects of\ndifferential geometry that exist not only in the classical category of smooth\nmanifolds but also in algebraic geometry, homological algebra, computer\nscience, and combinatorics. Generalizing the notion of (linear) connection on a\nsmooth vector bundle, Cockett and Cruttwell have defined a notion of connection\non a differential bundle in an arbitrary tangent category. Herein, we establish\nequivalent formulations of this notion of connection that reduce the amount of\nspecified structure required. Further, one of our equivalent formulations\nsubstantially reduces the number of axioms imposed, and others provide useful\nabstract conceptualizations of connections. In particular, we show that a\nconnection on a differential bundle E over M is equivalently given by a single\nmorphism K that induces a suitable decomposition of TE as a biproduct. We also\nshow that a connection is equivalently given by a vertical connection K for\nwhich a certain associated diagram is a limit diagram.\n",
"title": "On the geometric notion of connection and its expression in tangent categories"
} | null | null | null | null | true | null | 18349 | null | Default | null | null |
null | {
"abstract": " An objective Bayesian approach to estimate the number of degrees of freedom\n$(\\nu)$ for the multivariate $t$ distribution and for the $t$-copula, when the\nparameter is considered discrete, is proposed. Inference on this parameter has\nbeen problematic for the multivariate $t$ and, for the absence of any method,\nfor the $t$-copula. An objective criterion based on loss functions which allows\nto overcome the issue of defining objective probabilities directly is employed.\nThe support of the prior for $\\nu$ is truncated, which derives from the\nproperty of both the multivariate $t$ and the $t$-copula of convergence to\nnormality for a sufficiently large number of degrees of freedom. The\nperformance of the priors is tested on simulated scenarios. The R codes and the\nreplication material are available as a supplementary material of the\nelectronic version of the paper and on real data: daily logarithmic returns of\nIBM and of the Center for Research in Security Prices Database.\n",
"title": "Objective priors for the number of degrees of freedom of a multivariate t distribution and the t-copula"
} | null | null | null | null | true | null | 18350 | null | Default | null | null |
null | {
"abstract": " Navigation in unknown, chaotic environments continues to present a\nsignificant challenge for the robotics community. Lighting changes,\nself-similar textures, motion blur, and moving objects are all considerable\nstumbling blocks for state-of-the-art vision-based navigation algorithms. In\nthis paper we present a novel technique for improving localization accuracy\nwithin a visual-inertial navigation system (VINS). We make use of training data\nto learn a model for the quality of visual features with respect to\nlocalization error in a given environment. This model maps each visual\nobservation from a predefined prediction space of visual-inertial predictors\nonto a scalar weight, which is then used to scale the observation covariance\nmatrix. In this way, our model can adjust the influence of each observation\naccording to its quality. We discuss our choice of predictors and report\nsubstantial reductions in localization error on 4 km of data from the KITTI\ndataset, as well as on experimental datasets consisting of 700 m of indoor and\noutdoor driving on a small ground rover equipped with a Skybotix VI-Sensor.\n",
"title": "PROBE: Predictive Robust Estimation for Visual-Inertial Navigation"
} | null | null | null | null | true | null | 18351 | null | Default | null | null |
null | {
"abstract": " Artificial Intelligence (AI) is an effective science which employs strong\nenough approaches, methods, and techniques to solve unsolvable real world based\nproblems. Because of its unstoppable rise towards the future, there are also\nsome discussions about its ethics and safety. Shaping an AI friendly\nenvironment for people and a people friendly environment for AI can be a\npossible answer for finding a shared context of values for both humans and\nrobots. In this context, objective of this paper is to address the ethical\nissues of AI and explore the moral dilemmas that arise from ethical algorithms,\nfrom pre set or acquired values. In addition, the paper will also focus on the\nsubject of AI safety. As general, the paper will briefly analyze the concerns\nand potential solutions to solving the ethical issues presented and increase\nreaders awareness on AI safety as another related research interest.\n",
"title": "Ethical Artificial Intelligence - An Open Question"
} | null | null | null | null | true | null | 18352 | null | Default | null | null |
null | {
"abstract": " Headline generation is a special type of text summarization task. While the\namount of available training data for this task is almost unlimited, it still\nremains challenging, as learning to generate headlines for news articles\nimplies that the model has strong reasoning about natural language. To overcome\nthis issue, we applied recent Universal Transformer architecture paired with\nbyte-pair encoding technique and achieved new state-of-the-art results on the\nNew York Times Annotated corpus with ROUGE-L F1-score 24.84 and ROUGE-2\nF1-score 13.48. We also present the new RIA corpus and reach ROUGE-L F1-score\n36.81 and ROUGE-2 F1-score 22.15 on it.\n",
"title": "Self-Attentive Model for Headline Generation"
} | null | null | null | null | true | null | 18353 | null | Default | null | null |
null | {
"abstract": " We observed the Galactic mixed-morphology supernova remnant G166.0+4.3 with\nSuzaku. The X-ray spectrum in the western part of the remnant is well\nrepresented by a one-component ionizing plasma model. The spectrum in the\nnortheastern region can be explained by two components. One is the Fe-rich\ncomponent with the electron temperature $kT_e = 0.87_{-0.03}^{+0.02}$ keV. The\nother is the recombining plasma component of lighter elements with $kT_e =\n0.46\\pm0.03$ keV, the initial temperature $kT_{init} = 3$ keV (fixed) and the\nionization parameter $n_et = (6.1_{-0.4}^{+0.5}) \\times 10^{11} \\rm cm^{-3} s$.\nAs the formation process of the recombining plasma, two scenarios, the\nrarefaction and thermal conduction, are considered. The former would not be\nfavored since we found the recombining plasma only in the northeastern region\nwhereas the latter would explain the origin of the RP. In the latter scenario,\nan RP is anticipated in a part of the remnant where blast waves are in contact\nwith cool dense gas. The emission measure suggests higher ambient gas density\nin the northeastern region. The morphology of the radio shell and a GeV\ngamma-ray emission also suggest a molecular cloud in the region.\n",
"title": "Localized Recombining Plasma in G166.0+4.3: A Supernova Remnant with an Unusual Morphology"
} | null | null | null | null | true | null | 18354 | null | Default | null | null |
null | {
"abstract": " Software systems are not static, they have to undergo frequent changes to\nstay fit for purpose, and in the process of doing so, their complexity\nincreases. It has been observed that this process often leads to the erosion of\nthe systems design and architecture and with it, the decline of many desirable\nquality attributes, such as maintainability. This process can be captured in\nterms of antipatterns-atomic violations of widely accepted design principles.\nWe present a visualisation that exposes the design of evolving Java programs,\nhighlighting instances of selected antipatterns including their emergence and\ncancerous growth. This visualisation assists software engineers and architects\nin assessing, tracing and therefore combating design erosion. We evaluated the\neffectiveness of the visualisation in four case studies with ten participants.\n",
"title": "Visualizing Design Erosion: How Big Balls of Mud are Made"
} | null | null | [
"Computer Science"
]
| null | true | null | 18355 | null | Validated | null | null |
null | {
"abstract": " We explore efficient neural architecture search methods and show that a\nsimple yet powerful evolutionary algorithm can discover new architectures with\nexcellent performance. Our approach combines a novel hierarchical genetic\nrepresentation scheme that imitates the modularized design pattern commonly\nadopted by human experts, and an expressive search space that supports complex\ntopologies. Our algorithm efficiently discovers architectures that outperform a\nlarge number of manually designed models for image classification, obtaining\ntop-1 error of 3.6% on CIFAR-10 and 20.3% when transferred to ImageNet, which\nis competitive with the best existing neural architecture search approaches. We\nalso present results using random search, achieving 0.3% less top-1 accuracy on\nCIFAR-10 and 0.1% less on ImageNet whilst reducing the search time from 36\nhours down to 1 hour.\n",
"title": "Hierarchical Representations for Efficient Architecture Search"
} | null | null | null | null | true | null | 18356 | null | Default | null | null |
null | {
"abstract": " For the purpose of Uncertainty Quantification (UQ) of Reynolds-Averaged\nNavier-Stokes closures, we introduce a framework in which perturbations in the\neigenvalues of the anisotropy tensor are made in order to bound a\nQuantity-of-Interest based on limiting states of turbulence. To make the\nperturbations representative of local flow features, we introduce two\nadditional transport equations for linear combinations of these aforementioned\neigenvalues. The location, magnitude and direction of the eigenvalue\nperturbations are now governed by the model transport equations. The general\nbehavior of our discrepancy model is determined by two coefficients, resulting\nin a low-dimensional UQ problem. We will furthermore show that the behavior of\nthe model is intuitive and rooted in the physical interpretation of\nmisalignment between the mean strain and Reynolds stresses.\n",
"title": "A return to eddy viscosity model for epistemic UQ in RANS closures"
} | null | null | null | null | true | null | 18357 | null | Default | null | null |
null | {
"abstract": " We present here a new model and algorithm which performs an efficient Natural\ngradient descent for Multilayer Perceptrons. Natural gradient descent was\noriginally proposed from a point of view of information geometry, and it\nperforms the steepest descent updates on manifolds in a Riemannian space. In\nparticular, we extend an approach taken by the \"Whitened neural networks\"\nmodel. We make the whitening process not only in feed-forward direction as in\nthe original model, but also in the back-propagation phase. Its efficacy is\nshown by an application of this \"Bidirectional whitened neural networks\" model\nto a handwritten character recognition data (MNIST data).\n",
"title": "A Neural Network model with Bidirectional Whitening"
} | null | null | [
"Statistics"
]
| null | true | null | 18358 | null | Validated | null | null |
null | {
"abstract": " This paper studies the Sobolev regularity estimates of weak solutions of a\nclass of singular quasi-linear elliptic problems of the form $u_t -\n\\mbox{div}[\\mathbb{A}(x,t,u,\\nabla u)]= \\mbox{div}[{\\mathbf F}]$ with\nhomogeneous Dirichlet boundary conditions over bounded spatial domains. Our\nmain focus is on the case that the vector coefficients $\\mathbb{A}$ are\ndiscontinuous and singular in $(x,t)$-variables, and dependent on the solution\n$u$. Global and interior weighted $W^{1,p}(\\Omega, \\omega)$-regularity\nestimates are established for weak solutions of these equations, where $\\omega$\nis a weight function in some Muckenhoupt class of weights. The results obtained\nare even new for linear equations, and for $\\omega =1$, because of the\nsingularity of the coefficients in $(x,t)$-variables\n",
"title": "Regularity gradient estimates for weak solutions of singular quasi-linear parabolic equations"
} | null | null | null | null | true | null | 18359 | null | Default | null | null |
null | {
"abstract": " Despite recent advances, large scale visual artifacts are still a common\noccurrence in images generated by GANs. Previous work has focused on improving\nthe generator's capability to accurately imitate the data distribution\n$p_{data}$. In this paper, we instead explore methods that enable GANs to\nactively avoid errors by manipulating the input space. The core idea is to\napply small changes to each noise vector in order to shift them away from areas\nin the input space that tend to result in errors. We derive three different\narchitectures from that idea. The main one of these consists of a simple\nresidual module that leads to significantly less visual artifacts, while only\nslightly decreasing diversity. The module is trivial to add to existing GANs\nand costs almost zero computation and memory.\n",
"title": "Learning to Avoid Errors in GANs by Manipulating Input Spaces"
} | null | null | null | null | true | null | 18360 | null | Default | null | null |
null | {
"abstract": " This work proposes a process for efficiently searching over combinations of\nindividual object 6D pose hypotheses in cluttered scenes, especially in cases\ninvolving occlusions and objects resting on each other. The initial set of\ncandidate object poses is generated from state-of-the-art object detection and\nglobal point cloud registration techniques. The best-scored pose per object by\nusing these techniques may not be accurate due to overlaps and occlusions.\nNevertheless, experimental indications provided in this work show that object\nposes with lower ranks may be closer to the real poses than ones with high\nranks according to registration techniques. This motivates a global\noptimization process for improving these poses by taking into account\nscene-level physical interactions between objects. It also implies that the\nCartesian product of candidate poses for interacting objects must be searched\nso as to identify the best scene-level hypothesis. To perform the search\nefficiently, the candidate poses for each object are clustered so as to reduce\ntheir number but still keep a sufficient diversity. Then, searching over the\ncombinations of candidate object poses is performed through a Monte Carlo Tree\nSearch (MCTS) process that uses the similarity between the observed depth image\nof the scene and a rendering of the scene given the hypothesized pose as a\nscore that guides the search procedure. MCTS handles in a principled way the\ntradeoff between fine-tuning the most promising poses and exploring new ones,\nby using the Upper Confidence Bound (UCB) technique. Experimental results\nindicate that this process is able to quickly identify in cluttered scenes\nphysically-consistent object poses that are significantly closer to ground\ntruth compared to poses found by point cloud registration methods.\n",
"title": "Improving 6D Pose Estimation of Objects in Clutter via Physics-aware Monte Carlo Tree Search"
} | null | null | null | null | true | null | 18361 | null | Default | null | null |
null | {
"abstract": " The multi-label classification framework, where each observation can be\nassociated with a set of labels, has generated a tremendous amount of attention\nover recent years. The modern multi-label problems are typically large-scale in\nterms of number of observations, features and labels, and the amount of labels\ncan even be comparable with the amount of observations. In this context,\ndifferent remedies have been proposed to overcome the curse of dimensionality.\nIn this work, we aim at exploiting the output sparsity by introducing a new\nloss, called the sparse weighted Hamming loss. This proposed loss can be seen\nas a weighted version of classical ones, where active and inactive labels are\nweighted separately. Leveraging the influence of sparsity in the loss function,\nwe provide improved generalization bounds for the empirical risk minimizer, a\nsuitable property for large-scale problems. For this new loss, we derive rates\nof convergence linear in the underlying output-sparsity rather than linear in\nthe number of labels. In practice, minimizing the associated risk can be\nperformed efficiently by using convex surrogates and modern convex optimization\nalgorithms. We provide experiments on various real-world datasets demonstrating\nthe pertinence of our approach when compared to non-weighted techniques.\n",
"title": "On the benefits of output sparsity for multi-label classification"
} | null | null | null | null | true | null | 18362 | null | Default | null | null |
null | {
"abstract": " In this work we establish the tightest lower bound up-to-date for the minimal\ncrossing number of a satellite knot based on the minimal crossing number of the\ncompanion used to build the satellite. If $M$ is the wrapping number of the\npattern knot, we essentially show that $c(Sat(P,C))>\\frac{M^2}{2}c(C)$. The\nexistence of this bound will be proven when the companion knot is adequate, and\nit will be further tuned in the case of the companion being alternating.\n",
"title": "On wrapping number, adequacy and the crossing number of satellite knots"
} | null | null | null | null | true | null | 18363 | null | Default | null | null |
null | {
"abstract": " Web archives are large longitudinal collections that store webpages from the\npast, which might be missing on the current live Web. Consequently, temporal\nsearch over such collections is essential for finding prominent missing\nwebpages and tasks like historical analysis. However, this has been challenging\ndue to the lack of popularity information and proper ground truth to evaluate\ntemporal retrieval models. In this paper we investigate the applicability of\nexternal longitudinal resources to identify important and popular websites in\nthe past and analyze the social bookmarking service Delicious for this purpose.\nThe timestamped bookmarks on Delicious provide explicit cues about popular\ntime periods in the past along with relevant descriptors. These are valuable to\nidentify important documents in the past for a given temporal query. Focusing\npurely on recall, we analyzed more than 12,000 queries and find that using\nDelicious yields average recall values from 46% up to 100%, when limiting\nourselves to the best represented queries in the considered dataset. This\nconstitutes an attractive and low-overhead approach for quick access into Web\narchives by not dealing with the actual contents.\n",
"title": "On the Applicability of Delicious for Temporal Search on Web Archives"
} | null | null | null | null | true | null | 18364 | null | Default | null | null |
null | {
"abstract": " We begin by summarizing the relevance and importance of inductive analytics\nbased on the geometry and topology of data and information. Contemporary issues\nare then discussed. These include how sampling data for representativity is\nincreasingly to be questioned. While we can always avail of analytics from a\n\"bag of tools and techniques\", in the application of machine learning and\npredictive analytics, nonetheless we present the case for Bourdieu and\nBenzécri-based science of data, as follows. This is to construct bridges\nbetween data sources and position-taking, and decision-making. There is summary\npresentation of a few case studies, illustrating and exemplifying application\ndomains.\n",
"title": "The Geometry and Topology of Data and Information for Analytics of Processes and Behaviours: Building on Bourdieu and Addressing New Societal Challenges"
} | null | null | null | null | true | null | 18365 | null | Default | null | null |
null | {
"abstract": " Expanding upon earlier results [arXiv:1702.02861], we present a compendium of\n$\\sigma$-models associated with integrable deformations of AdS$_5$ generated by\nsolutions to homogenous classical Yang-Baxter equation. Each example we study\nfrom four viewpoints: conformal (Drinfeld) twists, closed string gravity\nbackgrounds, open string parameters and proposed dual noncommutative (NC) gauge\ntheory. Irrespective of whether the deformed background is a solution to\nsupergravity or generalized supergravity, we show that the open string metric\nassociated with each gravity background is undeformed AdS$_5$ with constant\nopen string coupling and the NC structure $\\Theta$ is directly related to the\nconformal twist. One novel feature is that $\\Theta$ exhibits \"holographic\nnoncommutativity\": while it may exhibit non-trivial dependence on the\nholographic direction, its value everywhere in the bulk is uniquely determined\nby its value at the boundary, thus facilitating introduction of a dual NC gauge\ntheory. We show that the divergence of the NC structure $\\Theta$ is directly\nrelated to the unimodularity of the twist. We discuss the implementation of an\nouter automorphism of the conformal algebra as a coordinate transformation in\nthe AdS bulk and discuss its implications for Yang-Baxter $\\sigma$-models and\nself-T-duality based on fermionic T-duality. Finally, we comment on\nimplications of our results for the integrability of associated open strings\nand planar integrability of dual NC gauge theories.\n",
"title": "Conformal Twists, Yang-Baxter $σ$-models & Holographic Noncommutativity"
} | null | null | null | null | true | null | 18366 | null | Default | null | null |
null | {
"abstract": " In this paper we present AWEsome (Airborne Wind Energy Standardized\nOpen-source Model Environment), a test platform for airborne wind energy\nsystems that consists of low-cost hardware and is entirely based on open-source\nsoftware. It can hence be used without the need of large financial investments,\nin particular by research groups and startups to acquire first experiences in\ntheir flight operations, to test novel control strategies or technical designs,\nor for usage in public relations. Our system consists of a modified\noff-the-shelf model aircraft that is controlled by the pixhawk autopilot\nhardware and the ardupilot software for fixed wing aircraft. The aircraft is\nattached to the ground by a tether. We have implemented new flight modes for\nthe autonomous tethered flight of the aircraft along periodic patterns. We\npresent the principal functionality of our algorithms. We report on first\nsuccessful tests of these modes in real flights.\n",
"title": "AWEsome: An open-source test platform for airborne wind energy systems"
} | null | null | [
"Computer Science"
]
| null | true | null | 18367 | null | Validated | null | null |
null | {
"abstract": " We propose a one-dimensional model for collecting lymphatics coupled with a\nnovel Electro-Fluid-Mechanical Contraction (EFMC) model for dynamical\ncontractions, based on a modified FitzHugh-Nagumo model for action potentials.\nThe one-dimensional model for a compliant lymphatic vessel is a set of\nhyperbolic Partial Differential Equations (PDEs). The EFMC model combines the\nelectrical activity of lymphangions (action potentials) with fluid-mechanical\nfeedback (stretch of the lymphatic wall and wall shear stress) and the\nmechanical variation of the lymphatic wall properties (contractions). The EFMC\nmodel is governed by four Ordinary Differential Equations (ODEs) and\nphenomenologically relies on: (1) environmental calcium influx, (2)\nstretch-activated calcium influx, and (3) contraction inhibitions induced by\nwall shear stresses. We carried out a complete mathematical analysis of the\nstability of the stationary state of the EFMC model. Overall, the EFMC model\nallows imitating the influence of pressure and wall shear stress on the\nfrequency of contractions observed experimentally. Lymphatic valves are\nmodelled using a well-established lumped-parameter model which allows\nsimulating stenotic and regurgitant valves. We analysed several lymphodynamical\nindexes of a single lymphangion for a wide range of upstream and downstream\npressure combinations. Stenotic and regurgitant valves were modelled, and their\neffects are here quantified. Results for stenotic valves showed in the\ndownstream lymphangion that for low frequencies of contractions the Calculated\nPump Flow (CPF) index remained almost unaltered, while for high frequencies the\nCPF dramatically decreased depending on the severity of the stenosis (up to 93%\nfor a severe stenosis). Results for incompetent valves showed that the net flow\nduring a lymphatic cycle tends to zero as the degree of incompetence increases.\n",
"title": "A one-dimensional mathematical model of collecting lymphatics coupled with an electro-fluid-mechanical contraction model and valve dynamics"
} | null | null | null | null | true | null | 18368 | null | Default | null | null |
null | {
"abstract": " We prove the existence of a one-parameter family of nondisplaceable\nLagrangian tori near a linear chain of Lagrangian 2-spheres in a symplectic\n4-manifold. When the symplectic structure is rational we prove that the\ndeformed Floer cohomology groups of these tori are nontrivial. The proof uses\nthe idea of toric degeneration to analyze the full potential functions with\nbulk deformations of these tori.\n",
"title": "$A_{n}$-type surface singularity and nondisplaceable Lagrangian tori"
} | null | null | null | null | true | null | 18369 | null | Default | null | null |
null | {
"abstract": " Haptic feedback is essential to acquire immersive experience when interacting\nin virtual or augmented reality. Although the existing promising magnetic\nlevitation (maglev) haptic system has advantages of none mechanical friction,\nits performance is limited by its navigation method, which mainly results from\nthe challenge that it is difficult to obtain high precision, high frame rate\nand good stability with lightweight design at the same. In this study, we\npropose to perform the visual-inertial fusion navigation based on\nsequence-to-sequence learning for the maglev haptic interaction. Cascade LSTM\nbased-increment learning method is first presented to progressively learn the\nincrements of the target variables. Then, two cascade LSTM networks are\nseparately trained for accomplishing the visual-inertial fusion navigation in a\nloosely-coupled mode. Additionally, we set up a maglev haptic platform as the\nsystem testbed. Experimental results show that the proposed cascade LSTM\nbased-increment learning method can achieve high-precision prediction, and our\ncascade LSTM based visual-inertial fusion navigation method can reach 200Hz\nwhile maintaining high-precision (the mean absolute error of the position and\norientation is respectively less than 1mm and 0.02°)navigation for the\nmaglev haptic interaction application.\n",
"title": "Cascade LSTM Based Visual-Inertial Navigation for Magnetic Levitation Haptic Interaction"
} | null | null | null | null | true | null | 18370 | null | Default | null | null |
null | {
"abstract": " Although the recent progress in the deep neural network has led to the\ndevelopment of learnable local feature descriptors, there is no explicit answer\nfor estimation of the necessary size of a neural network. Specifically, the\nlocal feature is represented in a low dimensional space, so the neural network\nshould have more compact structure. The small networks required for local\nfeature descriptor learning may be sensitive to initial conditions and learning\nparameters and more likely to become trapped in local minima. In order to\naddress the above problem, we introduce an adaptive pruning Siamese\nArchitecture based on neuron activation to learn local feature descriptors,\nmaking the network more computationally efficient with an improved recognition\nrate over more complex networks. Our experiments demonstrate that our learned\nlocal feature descriptors outperform the state-of-art methods in patch\nmatching.\n",
"title": "Local Feature Descriptor Learning with Adaptive Siamese Network"
} | null | null | null | null | true | null | 18371 | null | Default | null | null |
null | {
"abstract": " Recently, continuous cache models were proposed as extensions to recurrent\nneural network language models, to adapt their predictions to local changes in\nthe data distribution. These models only capture the local context, of up to a\nfew thousands tokens. In this paper, we propose an extension of continuous\ncache models, which can scale to larger contexts. In particular, we use a large\nscale non-parametric memory component that stores all the hidden activations\nseen in the past. We leverage recent advances in approximate nearest neighbor\nsearch and quantization algorithms to store millions of representations while\nsearching them efficiently. We conduct extensive experiments showing that our\napproach significantly improves the perplexity of pre-trained language models\non new distributions, and can scale efficiently to much larger contexts than\npreviously proposed local cache models.\n",
"title": "Unbounded cache model for online language modeling with open vocabulary"
} | null | null | null | null | true | null | 18372 | null | Default | null | null |
null | {
"abstract": " Dyson demonstrated an equivalence between infinite-range Coulomb gas models\nand classical random matrix ensembles for study of eigenvalue statistics. We\nintroduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process,\nand study them analytically and by Monte-Carlo simulations. These models yield\nnew universality classes, and provide a theoretical framework for study of\nbanded random matrices (BRM) and quantum kicked rotors (QKR). We demonstrate\nthat, for a BRM of bandwidth b and a QKR of chaos parameter {\\alpha}, the\nappropriate FRCG model has the effective range d = (b^2)/N = ({\\alpha}^2)/N,\nfor large N matrix dimensionality. As d increases, there is a transition from\nPoisson to classical random matrix statistics.\n",
"title": "Finite-Range Coulomb Gas Models of Banded Random Matrices and Quantum Kicked Rotors"
} | null | null | null | null | true | null | 18373 | null | Default | null | null |
null | {
"abstract": " We establish lower bounds on the volume and the surface area of a geometric\nbody using the size of its slices along different directions. In the first part\nof the paper, we derive volume bounds for convex bodies using generalized\nsubadditivity properties of entropy combined with entropy bounds for\nlog-concave random variables. In the second part, we investigate a new notion\nof Fisher information which we call the $L_1$-Fisher information, and show that\ncertain superadditivity properties of the $L_1$-Fisher information lead to\nlower bounds for the surface areas of polyconvex sets in terms of its slices.\n",
"title": "Dual Loomis-Whitney inequalities via information theory"
} | null | null | null | null | true | null | 18374 | null | Default | null | null |
null | {
"abstract": " A previously unreported Pb-based perovskite PbMoO$_3$ is obtained by\nhigh-pressure and high-temperature synthesis. This material crystallizes in the\n$Pm\\bar{3}m$ cubic structure at room temperature, making it distinct from\ntypical Pb-based perovskite oxides with a structural distortion. PbMoO$_3$\nexhibits a metallic behavior down to 0.1 K with an unusual $T$-sub linear\ndependence of the electrical resistivity. Moreover, a large specific heat is\nobserved at low temperatures accompanied by a peak in $C_P/T^3$ around 10 K, in\nmarked contrast to the isostructural metallic system SrMoO$_3$. These transport\nand thermal properties for PbMoO$_3$, taking into account anomalously large Pb\natomic displacements detected through diffraction experiments, are attributed\nto a low-energy vibrational mode, associated with incoherent off-centering of\nlone pair Pb$^{2+}$ cations. We discuss the unusual behavior of the electrical\nresistivity in terms of a polaron-like conduction, mediated by the strong\ncoupling between conduction electrons and optical phonons of the local\nlow-energy vibrational mode.\n",
"title": "Cubic lead perovskite PbMoO3 with anomalous metallic behavior"
} | null | null | [
"Physics"
]
| null | true | null | 18375 | null | Validated | null | null |
null | {
"abstract": " Most long memory forecasting studies assume that the memory is generated by\nthe fractional difference operator. We argue that the most cited theoretical\narguments for the presence of long memory do not imply the fractional\ndifference operator, and assess the performance of the autoregressive\nfractionally integrated moving average $(ARFIMA)$ model when forecasting series\nwith long memory generated by nonfractional processes. We find that high-order\nautoregressive $(AR)$ models produce similar or superior forecast performance\nthan $ARFIMA$ models at short horizons. Nonetheless, as the forecast horizon\nincreases, the $ARFIMA$ models tend to dominate in forecast performance. Hence,\n$ARFIMA$ models are well suited for forecasts of long memory processes\nregardless of the long memory generating mechanism, particularly for medium and\nlong forecast horizons. Additionally, we analyse the forecasting performance of\nthe heterogeneous autoregressive ($HAR$) model which imposes restrictions on\nhigh-order $AR$ models. We find that the structure imposed by the $HAR$ model\nproduces better long horizon forecasts than $AR$ models of the same order, at\nthe price of inferior short horizon forecasts in some cases. Our results have\nimplications for, among others, Climate Econometrics and Financial Econometrics\nmodels dealing with long memory series at different forecast horizons. We show\nin an example that while a short memory autoregressive moving average $(ARMA)$\nmodel gives the best performance when forecasting the Realized Variance of the\nS\\&P 500 up to a month ahead, the $ARFIMA$ model gives the best performance for\nlonger forecast horizons.\n",
"title": "On Long Memory Origins and Forecast Horizons"
} | null | null | null | null | true | null | 18376 | null | Default | null | null |
null | {
"abstract": " Source code plagiarism detection is a problem that has been addressed several\ntimes before; and several tools have been developed for that purpose. In this\nresearch project we investigated a set of possible disguises that can be\nmechanically applied to plagiarized source code to defeat plagiarism detection\ntools. We propose a preprocessor to be used with existing plagiarism detection\ntools to \"normalize\" source code before checking it, thus making such disguises\nineffective.\n",
"title": "Detecting Disguised Plagiarism"
} | null | null | [
"Computer Science"
]
| null | true | null | 18377 | null | Validated | null | null |
null | {
"abstract": " Early attempts to apply asteroseismology to study the Galaxy have already\nshown unexpected discrepancies for the mass distribution of stars between the\nGalactic models and the data; a result that is still unexplained. Here, we\nrevisit the analysis of the asteroseismic sample of dwarf and subgiant stars\nobserved by Kepler and investigate in detail the possible causes for the\nreported discrepancy. We investigate two models of the Milky Way based on\nstellar population synthesis, Galaxia and TRILEGAL. In agreement with previous\nresults, we find that TRILEGAL predicts more massive stars compared to Galaxia,\nand that TRILEGAL predicts too many blue stars compared to 2MASS observations.\nBoth models fail to match the distribution of the stellar sample in $(\\log\ng,T_{\\rm eff})$ space, pointing to inaccuracies in the models and/or the\nassumed selection function. When corrected for this mismatch in $(\\log g,T_{\\rm\neff})$ space, the mass distribution calculated by Galaxia is broader and the\nmean is shifted toward lower masses compared to that of the observed stars.\nThis behaviour is similar to what has been reported for the Kepler red giant\nsample. The shift between the mass distributions is equivalent to a change of\n2\\% in $\\nu_{\\rm max}$, which is within the current uncertainty in the\n$\\nu_{\\rm max}$ scaling relation. Applying corrections to the $\\Delta \\nu$\nscaling relation predicted by the stellar models makes the observed mass\ndistribution significantly narrower, but there is no change to the mean.\n",
"title": "Stellar population synthesis based modelling of the Milky Way using asteroseismology of dwarfs and subgiants from Kepler"
} | null | null | null | null | true | null | 18378 | null | Default | null | null |
null | {
"abstract": " Semantic labeling for numerical values is a task of assigning semantic labels\nto unknown numerical attributes. The semantic labels could be numerical\nproperties in ontologies, instances in knowledge bases, or labeled data that\nare manually annotated by domain experts. In this paper, we refer to semantic\nlabeling as a retrieval setting where the label of an unknown attribute is\nassigned by the label of the most relevant attribute in labeled data. One of\nthe greatest challenges is that an unknown attribute rarely has the same set of\nvalues with the similar one in the labeled data. To overcome the issue,\nstatistical interpretation of value distribution is taken into account.\nHowever, the existing studies assume a specific form of distribution. It is not\nappropriate in particular to apply open data where there is no knowledge of\ndata in advance. To address these problems, we propose a neural numerical\nembedding model (EmbNum) to learn useful representation vectors for numerical\nattributes without prior assumptions on the distribution of data. Then, the\n\"semantic similarities\" between the attributes are measured on these\nrepresentation vectors by the Euclidean distance. Our empirical experiments on\nCity Data and Open Data show that EmbNum significantly outperforms\nstate-of-the-art methods for the task of numerical attribute semantic labeling\nregarding effectiveness and efficiency.\n",
"title": "EmbNum: Semantic labeling for numerical values with deep metric learning"
} | null | null | null | null | true | null | 18379 | null | Default | null | null |
null | {
"abstract": " A statistical model assuming a preferential attachment network, which is\ngenerated by adding nodes sequentially according to a few simple rules, usually\ndescribes real-life networks better than a model assuming, for example, a\nBernoulli random graph, in which any two nodes have the same probability of\nbeing connected, does. Therefore, to study the propogation of \"infection\"\nacross a social network, we propose a network epidemic model by combining a\nstochastic epidemic model and a preferential attachment model. A simulation\nstudy based on the subsequent Markov Chain Monte Carlo algorithm reveals an\nidentifiability issue with the model parameters. Finally, the network epidemic\nmodel is applied to a set of online commissioning data.\n",
"title": "A Network Epidemic Model for Online Community Commissioning Data"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 18380 | null | Validated | null | null |
null | {
"abstract": " Descent theory for linear categories is developed. Given a linear category as\nan extension of a diagonal category, we introduce descent data, and the\ncategory of descent data is isomorphic to the category of representations of\nthe diagonal category, if some flatness assumptions are satisfied. Then\nHopf-Galois descent theory for linear Hopf categories, the Hopf algebra version\nof a linear category, is developed. This leads to the notion of Hopf-Galois\ncategory extension. We have a dual theory, where actions by dual linear Hopf\ncategories on linear categories are considered. Hopf-Galois category extensions\nover groupoid algebras correspond to strongly graded linear categories.\n",
"title": "Descent and Galois theory for Hopf categories"
} | null | null | null | null | true | null | 18381 | null | Default | null | null |
null | {
"abstract": " We give topological and game theoretic definitions and theorems nec- essary\nfor defining a Banach-Mazur game, and apply these definitions to formalize the\ngame. We then state and prove two theorems which give necessary conditions for\nexistence of winning strategies for players in a Banach-Mazur game.\n",
"title": "On winning strategies for Banach-Mazur games"
} | null | null | null | null | true | null | 18382 | null | Default | null | null |
null | {
"abstract": " Theory of the influence of the thermal fluctuations on the electric transport\nbeyond linear response in superconductors is developed within the framework of\nthe time dependent Ginzburg - Landau approach. The I - V curve is calculated\nusing the dynamical self - consistent gaussian approximation. Under certain\nconditions it exhibits a reentrant behaviour acquiring an S - shape form. The\nunstable region below a critical temperature $T^{\\ast }$ is determined for\narbitrary dimensionality ($D=1,2,3$) of the thermal fluctuations. The results\nare applied to analyse the transport data on nanowires and several classes of\n2D superconductors: metallic thin films, layered and atomically thick novel\nmaterials.\n",
"title": "Dynamical instability of the electric transport in strongly fluctuating superconductors"
} | null | null | null | null | true | null | 18383 | null | Default | null | null |
null | {
"abstract": " We demonstrate optomechanical interference in a multimode system, in which an\noptical mode couples to two mechanical modes. A phase-dependent\nexcitation-coupling approach is developed, which enables the observation of\nconstructive and destructive optomechanical interferences. The destructive\ninterference prevents the coupling of the mechanical system to the optical\nmode, suppressing optically-induced mechanical damping. These studies establish\noptomechanical interference as an essential tool for controlling the\ninteractions between light and mechanical oscillators.\n",
"title": "Controlling Multimode Optomechanical Interactions via Interference"
} | null | null | null | null | true | null | 18384 | null | Default | null | null |
null | {
"abstract": " We propose algorithms for online principal component analysis (PCA) and\nvariance minimization for adaptive settings. Previous literature has focused on\nupper bounding the static adversarial regret, whose comparator is the optimal\nfixed action in hindsight. However, static regret is not an appropriate metric\nwhen the underlying environment is changing. Instead, we adopt the adaptive\nregret metric from the previous literature and propose online adaptive\nalgorithms for PCA and variance minimization, that have sub-linear adaptive\nregret guarantees. We demonstrate both theoretically and experimentally that\nthe proposed algorithms can adapt to the changing environments.\n",
"title": "Online Adaptive Principal Component Analysis and Its extensions"
} | null | null | [
"Computer Science",
"Statistics"
]
| null | true | null | 18385 | null | Validated | null | null |
null | {
"abstract": " Cross-term spatiotemporal encoding (xSPEN) is a recently introduced imaging\napproach delivering single-scan 2D NMR images with unprecedented resilience to\nfield inhomogeneities. The method relies on performing a pre-acquisition\nencoding and a subsequent image read out while using the disturbing frequency\ninhomogeneities as part of the image formation processes, rather than as\nartifacts to be overwhelmed by the application of external gradients. This\nstudy introduces the use of this new single-shot MRI technique as a\ndiffusion-monitoring tool, for accessing regions that have hitherto been\nunapproachable by diffusion-weighted imaging (DWI) methods. In order to achieve\nthis, xSPEN MRIs intrinsic diffusion weighting effects are formulated using a\ncustomized, spatially-localized b-matrix analysis; with this, we devise a novel\ndiffusion-weighting scheme that both exploits and overcomes xSPENs strong\nintrinsic weighting effects. The ability to provide reliable and robust\ndiffusion maps in challenging head and brain regions, including the eyes and\nthe optic nerves, is thus demonstrated in humans at 3T; new avenues for imaging\nother body regions are also briefly discussed.\n",
"title": "Diffusion MRI measurements in challenging head and brain regions via cross-term spatiotemporally encoding"
} | null | null | null | null | true | null | 18386 | null | Default | null | null |
null | {
"abstract": " We derive formulas for the performance of capital assets in continuous time\nfrom an efficient market hypothesis, with no stochastic assumptions and no\nassumptions about the beliefs or preferences of investors. Our efficient market\nhypothesis says that a speculator with limited means cannot beat a particular\nindex by a substantial factor. Our results include a formula that resembles the\nclassical CAPM formula for the expected simple return of a security or\nportfolio.\nThis version of the article was essentially written in December 2001 but\nremains a working paper.\n",
"title": "Game-Theoretic Capital Asset Pricing in Continuous Time"
} | null | null | [
"Quantitative Finance"
]
| null | true | null | 18387 | null | Validated | null | null |
null | {
"abstract": " Apart from solving complicated problems that require a certain level of\nintelligence, fine-tuned deep neural networks can also create fast algorithms\nfor slow, numerical tasks. In this paper, we introduce an improved version of\n[1]'s work, a fast, deep-learning framework capable of generating the full\nworkspace of serial-link manipulators. The architecture consists of two neural\nnetworks: an estimation net that approximates the manipulator Jacobian, and a\nconfidence net that measures the confidence of the approximation. We also\nintroduce M3 (Manipulability Maps of Manipulators), a MATLAB robotics library\nbased on [2](RTB), the datasets generated by which are used by this work.\nResults have shown that not only are the neural networks significantly faster\nthan numerical inverse kinematics, it also offers superior accuracy when\ncompared to other machine learning alternatives. Implementations of the\nalgorithm (based on Keras[3]), including benchmark evaluation script, are\navailable at this https URL . The M3\nLibrary APIs and datasets are also available at\nthis https URL .\n",
"title": "Full Workspace Generation of Serial-link Manipulators by Deep Learning based Jacobian Estimation"
} | null | null | null | null | true | null | 18388 | null | Default | null | null |
null | {
"abstract": " This article considers algorithmic and statistical aspects of linear\nregression when the correspondence between the covariates and the responses is\nunknown. First, a fully polynomial-time approximation scheme is given for the\nnatural least squares optimization problem in any constant dimension. Next, in\nan average-case and noise-free setting where the responses exactly correspond\nto a linear function of i.i.d. draws from a standard multivariate normal\ndistribution, an efficient algorithm based on lattice basis reduction is shown\nto exactly recover the unknown linear function in arbitrary dimension. Finally,\nlower bounds on the signal-to-noise ratio are established for approximate\nrecovery of the unknown linear function by any estimator.\n",
"title": "Linear regression without correspondence"
} | null | null | null | null | true | null | 18389 | null | Default | null | null |
null | {
"abstract": " Privacy has become a serious concern for modern Information Societies. The\nsensitive nature of much of the data that are daily exchanged or released to\nuntrusted parties requires that responsible organizations undertake appropriate\nprivacy protection measures. Nowadays, much of these data are texts (e.g.,\nemails, messages posted in social media, healthcare outcomes, etc.) that,\nbecause of their unstructured and semantic nature, constitute a challenge for\nautomatic data protection methods. In fact, textual documents are usually\nprotected manually, in a process known as document redaction or sanitization.\nTo do so, human experts identify sensitive terms (i.e., terms that may reveal\nidentities and/or confidential information) and protect them accordingly (e.g.,\nvia removal or, preferably, generalization). To relieve experts from this\nburdensome task, in a previous work we introduced the theoretical basis of\nC-sanitization, an inherently semantic privacy model that provides the basis to\nthe development of automatic document redaction/sanitization algorithms and\noffers clear and a priori privacy guarantees on data protection; even though\nits potential benefits C-sanitization still presents some limitations when\napplied to practice (mainly regarding flexibility, efficiency and accuracy). In\nthis paper, we propose a new more flexible model, named (C, g(C))-sanitization,\nwhich enables an intuitive configuration of the trade-off between the desired\nlevel of protection (i.e., controlled information disclosure) and the\npreservation of the utility of the protected data (i.e., amount of semantics to\nbe preserved). Moreover, we also present a set of technical solutions and\nalgorithms that provide an efficient and scalable implementation of the model\nand improve its practical accuracy, as we also illustrate through empirical\nexperiments.\n",
"title": "Toward sensitive document release with privacy guarantees"
} | null | null | null | null | true | null | 18390 | null | Default | null | null |
null | {
"abstract": " We give a brief description of the Birch-Swinnerton-Dyer conjecture and\npresent related conjectures. We describe the relation between the nilpotent\norbits of SL(2,R) and CM points.\n",
"title": "Remarks on the Birch-Swinnerton-Dyer conjecture"
} | null | null | null | null | true | null | 18391 | null | Default | null | null |
null | {
"abstract": " Unmanned aerial vehicles (UAVs) have gained a lot of popularity in diverse\nwireless communication fields. They can act as high-altitude flying relays to\nsupport communications between ground nodes due to their ability to provide\nline-of-sight links. With the flourishing Internet of Things, several types of\nnew applications are emerging. In this paper, we focus on bandwidth hungry and\ndelay-tolerant applications where multiple pairs of transceivers require the\nsupport of UAVs to complete their transmissions. To do so, the UAVs have the\npossibility to employ two different bands namely the typical microwave and the\nhigh-rate millimeter wave bands. In this paper, we develop a generic framework\nto assign UAVs to supported transceivers and optimize their trajectories such\nthat a weighted function of the total service time is minimized. Taking into\naccount both the communication time needed to relay the message and the flying\ntime of the UAVs, a mixed non-linear programming problem aiming at finding the\nstops at which the UAVs hover to forward the data to the receivers is\nformulated. An iterative approach is then developed to solve the problem.\nFirst, a mixed linear programming problem is optimally solved to determine the\npath of each available UAV. Then, a hierarchical iterative search is executed\nto enhance the UAV stops' locations and reduce the service time. The behavior\nof the UAVs and the benefits of the proposed framework are showcased for\nselected scenarios.\n",
"title": "Trajectory Optimization for Cooperative Dual-band UAV Swarms"
} | null | null | null | null | true | null | 18392 | null | Default | null | null |
null | {
"abstract": " We present a denotational account of dynamic allocation of potentially cyclic\nmemory cells using a monad on a functor category. We identify the collection of\nheaps as an object in a different functor category equipped with a monad for\nadding hiding/encapsulation capabilities to the heaps. We derive a monad for\nfull ground references supporting effect masking by applying a state monad\ntransformer to the encapsulation monad. To evaluate the monad, we present a\ndenotational semantics for a call-by-value calculus with full ground\nreferences, and validate associated code transformations.\n",
"title": "A monad for full ground reference cells"
} | null | null | [
"Computer Science",
"Mathematics"
]
| null | true | null | 18393 | null | Validated | null | null |
null | {
"abstract": " Deep networks thrive when trained on large scale data collections. This has\ngiven ImageNet a central role in the development of deep architectures for\nvisual object classification. However, ImageNet was created during a specific\nperiod in time, and as such it is prone to aging, as well as dataset bias\nissues. Moving beyond fixed training datasets will lead to more robust visual\nsystems, especially when deployed on robots in new environments which must\ntrain on the objects they encounter there. To make this possible, it is\nimportant to break free from the need for manual annotators. Recent work has\nbegun to investigate how to use the massive amount of images available on the\nWeb in place of manual image annotations. We contribute to this research thread\nwith two findings: (1) a study correlating a given level of noisily labels to\nthe expected drop in accuracy, for two deep architectures, on two different\ntypes of noise, that clearly identifies GoogLeNet as a suitable architecture\nfor learning from Web data; (2) a recipe for the creation of Web datasets with\nminimal noise and maximum visual variability, based on a visual and natural\nlanguage processing concept expansion strategy. By combining these two results,\nwe obtain a method for learning powerful deep object models automatically from\nthe Web. We confirm the effectiveness of our approach through object\ncategorization experiments using our Web-derived version of ImageNet on a\npopular robot vision benchmark database, and on a lifelong object discovery\ntask on a mobile robot.\n",
"title": "Learning Deep Visual Object Models From Noisy Web Data: How to Make it Work"
} | null | null | null | null | true | null | 18394 | null | Default | null | null |
null | {
"abstract": " In the restricted three-body problem, consecutive collision orbits are those\norbits which start and end at collisions with one of the primaries. Interests\nfor such orbits arise not only from mathematics but also from various\nengineering problems. In this article, using Floer homology, we show that there\nare either a periodic collisional orbit, or infinitely many consecutive\ncollision orbits in the planar circular restricted three-body problem on each\nbounded component of the energy hypersurface for Jacobi energy below the first\ncritical value.\n",
"title": "Existence of either a periodic collisional orbit or infinitely many consecutive collision orbits in the planar circular restricted three-body problem"
} | null | null | null | null | true | null | 18395 | null | Default | null | null |
null | {
"abstract": " This paper presents the notion of AND-OR reduction, which reduces a WF net to\na smaller net by iteratively contracting certain well-formed subnets into\nsingle nodes until no more such contractions are possible. This reduction can\nreveal the hierarchical structure of a WF net, and since it preserves certain\nsemantical properties such as soundness, it can help with analysing and\nunderstanding why a WF net is sound or not. The reduction can also be used to\nverify if a WF net is an AND-OR net. This class of WF nets was introduced in\nearlier work, and arguably describes nets that follow good hierarchical design\nprinciples. It is shown that the AND-OR reduction is confluent up to\nisomorphism, which means that despite the inherent non-determinism that comes\nfrom the choice of subnets that are contracted, the final result of the\nreduction is always the same up to the choice of the identity of the nodes.\nBased on this result, a polynomial-time algorithm is presented that computes\nthis unique result of the AND-OR reduction. Finally, it is shown how this\nalgorithm can be used to verify if a WF net is an AND-OR net.\n",
"title": "Finding AND-OR Hierarchies in Workflow Nets"
} | null | null | null | null | true | null | 18396 | null | Default | null | null |
null | {
"abstract": " The present work shows the application of transfer learning for a pre-trained\ndeep neural network (DNN), using a small image dataset ($\\approx$ 12,000) on a\nsingle workstation with enabled NVIDIA GPU card that takes up to 1 hour to\ncomplete the training task and archive an overall average accuracy of $94.7\\%$.\nThe DNN presents a $20\\%$ score of misclassification for an external test\ndataset. The accuracy of the proposed methodology is equivalent to ones using\nHSI methodology $(81\\%-91\\%)$ used for the same task, but with the advantage of\nbeing independent on special equipment to classify wheat kernel for FHB\nsymptoms.\n",
"title": "Fusarium Damaged Kernels Detection Using Transfer Learning on Deep Neural Network Architecture"
} | null | null | null | null | true | null | 18397 | null | Default | null | null |
null | {
"abstract": " In this paper, we study simple splines on a Riemannian manifold $Q$ from the\npoint of view of the Pontryagin maximum principle (PMP) in optimal control\ntheory. The control problem consists in finding smooth curves matching two\ngiven tangent vectors with the control being the curve's acceleration, while\nminimizing a given cost functional. We focus on cubic splines (quadratic cost\nfunction) and on time-minimal splines (constant cost function) under bounded\nacceleration. We present a general strategy to solve for the optimal\nhamiltonian within the PMP framework based on splitting the variables by means\nof a linear connection. We write down the corresponding hamiltonian equations\nin intrinsic form and study the corresponding hamiltonian dynamics in the case\n$Q$ is the $2$-sphere. We also elaborate on possible applications, including\nlandmark cometrics in computational anatomy.\n",
"title": "About simple variational splines from the Hamiltonian viewpoint"
} | null | null | null | null | true | null | 18398 | null | Default | null | null |
null | {
"abstract": " The hand is one of the most complex and important parts of the human body.\nThe dexterity provided by its multiple degrees of freedom enables us to perform\nmany of the tasks of daily living which involve grasping and manipulating\nobjects of interest. Contemporary prosthetic devices for people with\ntransradial amputations or wrist disarticulation vary in complexity, from\npassive prosthetics to complex devices that are body or electrically driven.\nOne of the important challenges in developing smart prosthetic hands is to\ncreate devices which are able to mimic all activities that a person might\nperform and address the needs of a wide variety of users. The approach explored\nhere is to develop algorithms that permit a device to adapt its behavior to the\npreferences of the operator through interactions with the wearer. This device\nuses multiple sensing modalities including muscle activity from a myoelectric\narmband, visual information from an on-board camera, tactile input through a\ntouchscreen interface, and speech input from an embedded microphone. Presented\nwithin this paper are the design, software and controls of a platform used to\nevaluate this architecture as well as results from experiments deigned to\nquantify the performance.\n",
"title": "Adaptive Grasp Control through Multi-Modal Interactions for Assistive Prosthetic Devices"
} | null | null | null | null | true | null | 18399 | null | Default | null | null |
null | {
"abstract": " We study the popular centrality measure known as effective conductance or in\nsome circles as information centrality. This is an important notion of\ncentrality for undirected networks, with many applications, e.g., for random\nwalks, electrical resistor networks, epidemic spreading, etc. In this paper, we\nfirst reinterpret this measure in terms of modulus (energy) of families of\nwalks on the network. This modulus centrality measure coincides with the\neffective conductance measure on simple undirected networks, and extends it to\nmuch more general situations, e.g., directed networks as well. Secondly, we\nstudy a variation of this modulus approach in the egocentric network paradigm.\nEgonetworks are networks formed around a focal node (ego) with a specific order\nof neighborhoods. We propose efficient analytical and approximate methods for\ncomputing these measures on both undirected and directed networks. Finally, we\ndescribe a simple method inspired by the modulus point-of-view, called shell\ndegree, which proved to be a useful tool for network science.\n",
"title": "Generalization of Effective Conductance Centrality for Egonetworks"
} | null | null | null | null | true | null | 18400 | null | Default | null | null |
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