52,182 research outputs found
Early Warning Analysis for Social Diffusion Events
There is considerable interest in developing predictive capabilities for
social diffusion processes, for instance to permit early identification of
emerging contentious situations, rapid detection of disease outbreaks, or
accurate forecasting of the ultimate reach of potentially viral ideas or
behaviors. This paper proposes a new approach to this predictive analytics
problem, in which analysis of meso-scale network dynamics is leveraged to
generate useful predictions for complex social phenomena. We begin by deriving
a stochastic hybrid dynamical systems (S-HDS) model for diffusion processes
taking place over social networks with realistic topologies; this modeling
approach is inspired by recent work in biology demonstrating that S-HDS offer a
useful mathematical formalism with which to represent complex, multi-scale
biological network dynamics. We then perform formal stochastic reachability
analysis with this S-HDS model and conclude that the outcomes of social
diffusion processes may depend crucially upon the way the early dynamics of the
process interacts with the underlying network's community structure and
core-periphery structure. This theoretical finding provides the foundations for
developing a machine learning algorithm that enables accurate early warning
analysis for social diffusion events. The utility of the warning algorithm, and
the power of network-based predictive metrics, are demonstrated through an
empirical investigation of the propagation of political memes over social media
networks. Additionally, we illustrate the potential of the approach for
security informatics applications through case studies involving early warning
analysis of large-scale protests events and politically-motivated cyber
attacks
Waveguide physical modeling of vocal tract acoustics: flexible formant bandwidth control from increased model dimensionality
Digital waveguide physical modeling is often used as an efficient representation of acoustical resonators such as the human vocal tract. Building on the basic one-dimensional (1-D) Kelly-Lochbaum tract model, various speech synthesis techniques demonstrate improvements to the wave scattering mechanisms in order to better approximate wave propagation in the complex vocal system. Some of these techniques are discussed in this paper, with particular reference to an alternative approach in the form of a two-dimensional waveguide mesh model. Emphasis is placed on its ability to produce vowel spectra similar to that which would be present in natural speech, and how it improves upon the 1-D model. Tract area function is accommodated as model width, rather than translated into acoustic impedance, and as such offers extra control as an additional bounding limit to the model. Results show that the two-dimensional (2-D) model introduces approximately linear control over formant bandwidths leading to attainable realistic values across a range of vowels. Similarly, the 2-D model allows for application of theoretical reflection values within the tract, which when applied to the 1-D model result in small formant bandwidths, and, hence, unnatural sounding synthesized vowels
Correlated Prompt Fission Data in Transport Simulations
Detailed information on the fission process can be inferred from the
observation, modeling and theoretical understanding of prompt fission neutron
and -ray~observables. Beyond simple average quantities, the study of
distributions and correlations in prompt data, e.g., multiplicity-dependent
neutron and \gray~spectra, angular distributions of the emitted particles,
-, -, and -~correlations, can place stringent
constraints on fission models and parameters that would otherwise be free to be
tuned separately to represent individual fission observables. The FREYA~and
CGMF~codes have been developed to follow the sequential emissions of prompt
neutrons and -rays~from the initial excited fission fragments produced
right after scission. Both codes implement Monte Carlo techniques to sample
initial fission fragment configurations in mass, charge and kinetic energy and
sample probabilities of neutron and ~emission at each stage of the
decay. This approach naturally leads to using simple but powerful statistical
techniques to infer distributions and correlations among many observables and
model parameters. The comparison of model calculations with experimental data
provides a rich arena for testing various nuclear physics models such as those
related to the nuclear structure and level densities of neutron-rich nuclei,
the -ray~strength functions of dipole and quadrupole transitions, the
mechanism for dividing the excitation energy between the two nascent fragments
near scission, and the mechanisms behind the production of angular momentum in
the fragments, etc. Beyond the obvious interest from a fundamental physics
point of view, such studies are also important for addressing data needs in
various nuclear applications. (See text for full abstract.)Comment: 39 pages, 57 figure files, published in Eur. Phys. J. A, reference
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