75,812 research outputs found
Simulated evaluation of faceted browsing based on feature selection
In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness
Cluster-based reduced-order modelling of a mixing layer
We propose a novel cluster-based reduced-order modelling (CROM) strategy of
unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger's
group (Burkardt et al. 2006) and and transition matrix models introduced in
fluid dynamics in Eckhardt's group (Schneider et al. 2007). CROM constitutes a
potential alternative to POD models and generalises the Ulam-Galerkin method
classically used in dynamical systems to determine a finite-rank approximation
of the Perron-Frobenius operator. The proposed strategy processes a
time-resolved sequence of flow snapshots in two steps. First, the snapshot data
are clustered into a small number of representative states, called centroids,
in the state space. These centroids partition the state space in complementary
non-overlapping regions (centroidal Voronoi cells). Departing from the standard
algorithm, the probabilities of the clusters are determined, and the states are
sorted by analysis of the transition matrix. Secondly, the transitions between
the states are dynamically modelled using a Markov process. Physical mechanisms
are then distilled by a refined analysis of the Markov process, e.g. using
finite-time Lyapunov exponent and entropic methods. This CROM framework is
applied to the Lorenz attractor (as illustrative example), to velocity fields
of the spatially evolving incompressible mixing layer and the three-dimensional
turbulent wake of a bluff body. For these examples, CROM is shown to identify
non-trivial quasi-attractors and transition processes in an unsupervised
manner. CROM has numerous potential applications for the systematic
identification of physical mechanisms of complex dynamics, for comparison of
flow evolution models, for the identification of precursors to desirable and
undesirable events, and for flow control applications exploiting nonlinear
actuation dynamics.Comment: 48 pages, 30 figures. Revised version with additional material.
Accepted for publication in Journal of Fluid Mechanic
Facet-Based Browsing in Video Retrieval: A Simulation-Based Evaluation
In this paper we introduce a novel interactive video retrieval approach which uses sub-needs of an information need for querying and organising the search process. The underlying assumption of this approach is that the search effectiveness will be enhanced when employed for interactive video retrieval. We explore the performance bounds of a faceted system by using the simulated user evaluation methodology on TRECVID data sets and also on the logs of a prior user experiment with the system. We discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. The facets are simulated by the use of clustering the video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness
Voronoi Tessellations and the Cosmic Web: Spatial Patterns and Clustering across the Universe
The spatial cosmic matter distribution on scales of a few up to more than a
hundred Megaparsec displays a salient and pervasive foamlike pattern. Voronoi
tessellations are a versatile and flexible mathematical model for such weblike
spatial patterns. They would be the natural asymptotic result of an evolution
in which low-density expanding void regions dictate the spatial organization of
the Megaparsec Universe, while matter assembles in high-density filamentary and
wall-like interstices between the voids. We describe the results of ongoing
investigations of a variety of aspects of cosmologically relevant spatial
distributions and statistics within the framework of Voronoi tessellations.
Particularly enticing is the finding of a profound scaling of both clustering
strength and clustering extent for the distribution of tessellation nodes,
suggestive for the clustering properties of galaxy clusters. Cellular patterns
may be the source of an intrinsic ``geometrically biased'' clustering.Comment: 10 pages, 9 figures, accepted for publication as long paper in
proceedings Fourth International Symposium on Voronoi Diagrams in Science and
Engineering (ISVD 2007), ed. C. Gold, IEEE Computer Society, July 2007. For
high-res version see
http://www.astro.rug.nl/~weygaert/tim1publication/vorwey.isvd07.pd
The Dark Energy Survey
We describe the Dark Energy Survey (DES), a proposed optical-near infrared
survey of 5000 sq. deg of the South Galactic Cap to ~24th magnitude in SDSS
griz, that would use a new 3 sq. deg CCD camera to be mounted on the Blanco 4-m
telescope at Cerro Telolo Inter-American Observatory (CTIO). The survey data
will allow us to measure the dark energy and dark matter densities and the dark
energy equation of state through four independent methods: galaxy clusters,
weak gravitational lensing tomography, galaxy angular clustering, and supernova
distances. These methods are doubly complementary: they constrain different
combinations of cosmological model parameters and are subject to different
systematic errors. By deriving the four sets of measurements from the same data
set with a common analysis framework, we will obtain important cross checks of
the systematic errors and thereby make a substantial and robust advance in the
precision of dark energy measurements.Comment: White Paper submitted to the Dark Energy Task Force, 42 page
Macroscopic Noisy Bounded Confidence Models with Distributed Radical Opinions
In this article, we study the nonlinear Fokker-Planck (FP) equation that
arises as a mean-field (macroscopic) approximation of bounded confidence
opinion dynamics, where opinions are influenced by environmental noises and
opinions of radicals (stubborn individuals). The distribution of radical
opinions serves as an infinite-dimensional exogenous input to the FP equation,
visibly influencing the steady opinion profile. We establish mathematical
properties of the FP equation. In particular, we (i) show the well-posedness of
the dynamic equation, (ii) provide existence result accompanied by a
quantitative global estimate for the corresponding stationary solution, and
(iii) establish an explicit lower bound on the noise level that guarantees
exponential convergence of the dynamics to stationary state. Combining the
results in (ii) and (iii) readily yields the input-output stability of the
system for sufficiently large noises. Next, using Fourier analysis, the
structure of opinion clusters under the uniform initial distribution is
examined. Specifically, two numerical schemes for identification of
order-disorder transition and characterization of initial clustering behavior
are provided. The results of analysis are validated through several numerical
simulations of the continuum-agent model (partial differential equation) and
the corresponding discrete-agent model (interacting stochastic differential
equations) for a particular distribution of radicals
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