9,870 research outputs found
Using noun phrases extraction for the improvement of hybrid clustering with text- and citation-based components. The example of âInformation Systems Researchâ
The hybrid clustering approach combining lexical and link-based similarities suffered for a long time from the different properties of the underlying networks. We propose a method based on noun phrase extraction using natural language processing to improve the measurement of the lexical component. Term shingles of different length are created form each of the extracted noun phrases. Hybrid networks are built based on weighted combination of the two types of similarities with seven different weights. We conclude that removing all single term shingles provides the best results at the level of computational feasibility, comparability with bibliographic coupling and also in a community detection application
Perturbations of vortex ring pairs
We study pairs of co-axial vortex rings starting from the action for a
classical bosonic string in a three-form background. We complete earlier work
on the phase diagram of classical orbits by explicitly considering the case
where the circulations of the two vortex rings are equal and opposite. We then
go on to study perturbations, focusing on cases where the relevant
four-dimensional transfer matrix splits into two-dimensional blocks. When the
circulations of the rings have the same sign, instabilities are mostly limited
to wavelengths smaller than a dynamically generated length scale at which
single-ring instabilities occur. When the circulations have the opposite sign,
larger wavelength instabilities can occur.Comment: 62 pages, 21 figure
Predicting coexistence of plants subject to a tolerance-competition trade-off
Ecological trade-offs between species are often invoked to explain species
coexistence in ecological communities. However, few mathematical models have
been proposed for which coexistence conditions can be characterized explicitly
in terms of a trade-off. Here we present a model of a plant community which
allows such a characterization. In the model plant species compete for sites
where each site has a fixed stress condition. Species differ both in stress
tolerance and competitive ability. Stress tolerance is quantified as the
fraction of sites with stress conditions low enough to allow establishment.
Competitive ability is quantified as the propensity to win the competition for
empty sites. We derive the deterministic, discrete-time dynamical system for
the species abundances. We prove the conditions under which plant species can
coexist in a stable equilibrium. We show that the coexistence conditions can be
characterized graphically, clearly illustrating the trade-off between stress
tolerance and competitive ability. We compare our model with a recently
proposed, continuous-time dynamical system for a tolerance-fecundity trade-off
in plant communities, and we show that this model is a special case of the
continuous-time version of our model.Comment: To be published in Journal of Mathematical Biology. 30 pages, 5
figures, 5 appendice
Stability of constant retrial rate systems with NBU input*
We study the stability of a single-server retrial queueing system with constant retrial rate, general input and service processes. First, we present a review of some relevant recent results related to the stability criteria of similar systems. Sufficient stability conditions were obtained by Avrachenkov and Morozov (2014), which hold for a rather general retrial system. However, only in the case of Poisson input is an explicit expression provided; otherwise one has to rely on simulation. On the other hand, the stability criteria derived by Lillo (1996) can be easily computed but only hold for the case of exponential service times. We present new sufficient stability conditions, which are less tight than the ones obtained by Avrachenkov and Morozov (2010), but have an analytical expression under rather general assumptions. A key assumption is that interarrival times belongs to the class of new better than used (NBU) distributions. We illustrate the accuracy of the condition based on this assumption (in comparison with known conditions when possible) for a number of non-exponential distributions
Coherent supercontinuum generation in a silicon photonic wire in the telecommunication wavelength range
We demonstrate a fully coherent supercontinuum spectrum spanning 500 nm from a silicon-on-insulator photonic wire waveguide pumped at 1575 nm wavelength. An excellent agreement with numerical simulations is reported. The simulations also show that a high level of two-photon absorption can essentially enforce the coherence of the spectral broadening process irrespective of the pump pulse duration.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
Aggregate real wages: macro fluctuations and micro drivers
Using data from the Current Population Survey from 1980 through 2010 we examine what drives variation and cyclicality in the growth rate of real wages over time. We employ a novel decomposition technique that allows us to divide the time series for median weekly earnings growth into the part associated with the wage growth of persons employed at the beginning and end of the period (the wage growth effect) and the part associated with changes in the composition of earners (the composition effect). The relative importance of these two effects varies widely over the business cycle. When the labor market is tight job switchers get high wage increases, making them account for half of the variation in median weekly earnings growth over our sample. Their wage growth, as well as that of job-stayers, is procyclical. During labor market downturns, this procyclicality is largely offset by the change in the composition of the workforce, leading aggregate real wages to be almost noncyclical. Most of this composition effect works through the part-time employment margin. Remarkably, the unemployment margin neither accounts for much of the variation nor for much of the cyclicality of median weekly earnings growth.Wages ; Labor market
Band gap prediction for large organic crystal structures with machine learning
Machine-learning models are capable of capturing the structure-property
relationship from a dataset of computationally demanding ab initio
calculations. Over the past two years, the Organic Materials Database (OMDB)
has hosted a growing number of calculated electronic properties of previously
synthesized organic crystal structures. The complexity of the organic crystals
contained within the OMDB, which have on average 82 atoms per unit cell, makes
this database a challenging platform for machine learning applications. In this
paper, the focus is on predicting the band gap which represents one of the
basic properties of a crystalline materials. With this aim, a consistent
dataset of 12 500 crystal structures and their corresponding DFT band gap are
released, freely available for download at https://omdb.mathub.io/dataset. An
ensemble of two state-of-the-art models reach a mean absolute error (MAE) of
0.388 eV, which corresponds to a percentage error of 13% for an average band
gap of 3.05 eV. Finally, the trained models are employed to predict the band
gap for 260 092 materials contained within the Crystallography Open Database
(COD) and made available online so that the predictions can be obtained for any
arbitrary crystal structure uploaded by a user.Comment: 10 pages, 6 figure
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