267 research outputs found
Data visualization: foundations, techniques, and applications
The idea that there is no precedence for the amount of data that is being generated
today, and that the need to explore and analyze this vast volumes of data has become an
increasingly difficult task that could benefit from using Data visualization is presented. It is
pointed that the goals of data visualization are data-driven and depend largely on the type
of application, but the final objective is to convey to people information that is hidden in
large volumes of data. Finally, the visualization pipeline is presented to review aspects of
visualization methodology and visualization tool design, to conclude that the true potential of
visualization emerge from the interaction of the user with the visualization model. The paper
concludes establishing that the current processes of digital transformation will increase the
need for visual analytics tools
Dust and gas emission from cometary nuclei: the case of comet 67P/Churyumov-Gerasimenko
Comets display with decreasing solar distance an increased emission of gas
and dust particles, leading to the formation of the coma and tail. Spacecraft
missions provide insight in the temporal and spatial variations of the dust and
gas sources located on the cometary nucleus. For the case of comet
67P/Churyumov-Gerasimenko (67P/C-G), the long-term observations from the
Rosetta mission point to a homogeneous dust emission across the entire
illuminated surface. Despite the homogeneous initial distribution, a
collimation in jet-like structures becomes visible. We propose that this
observation is linked directly to the complex shape of the nucleus and projects
concave topographical features into the dust coma. To test this hypothesis, we
put forward a gas-dust description of 67P/C-G, where gravitational and gas
forces are accurately determined from the surface mesh and the rotation of the
nucleus is fully incorporated. The emerging jet-like structures persist for a
wide range of gas-dust interactions and show a dust velocity dependent bending.Comment: 17 pages, with 7 figures. To appear in Advances in Physics X (2018
Bi-invariant Dissimilarity Measures for Sample Distributions in Lie Groups
Data sets sampled in Lie groups are widespread, and as with multivariate
data, it is important for many applications to assess the differences between
the sets in terms of their distributions. Indices for this task are usually
derived by considering the Lie group as a Riemannian manifold. Then, however,
compatibility with the group operation is guaranteed only if a bi-invariant
metric exists, which is not the case for most non-compact and non-commutative
groups. We show here that if one considers an affine connection structure
instead, one obtains bi-invariant generalizations of well-known dissimilarity
measures: a Hotelling statistic, Bhattacharyya distance and Hellinger
distance. Each of the dissimilarity measures matches its multivariate
counterpart for Euclidean data and is translation-invariant, so that biases,
e.g., through an arbitrary choice of reference, are avoided. We further derive
non-parametric two-sample tests that are bi-invariant and consistent. We
demonstrate the potential of these dissimilarity measures by performing group
tests on data of knee configurations and epidemiological shape data.
Significant differences are revealed in both cases.Comment: An incomplete (and thus incorrect) statement in the background
section on the connection of the CCS connection to Riemannian metrics was
corrected. It was not used anywhere in the pape
Exploring cavity dynamics in biomolecular systems
Background The internal cavities of proteins are dynamic structures and their
dynamics may be associated with conformational changes which are required for
the functioning of the protein. In order to study the dynamics of these
internal protein cavities, appropriate tools are required that allow rapid
identification of the cavities as well as assessment of their time-dependent
structures. Results In this paper, we present such a tool and give results
that illustrate the applicability for the analysis of molecular dynamics
trajectories. Our algorithm consists of a pre-processing step where the
structure of the cavity is computed from the Voronoi diagram of the van der
Waals spheres based on coordinate sets from the molecular dynamics trajectory.
The pre-processing step is followed by an interactive stage, where the user
can compute, select and visualize the dynamic cavities. Importantly, the tool
we discuss here allows the user to analyze the time-dependent changes of the
components of the cavity structure. An overview of the cavity dynamics is
derived by rendering the dynamic cavities in a single image that gives the
cavity surface colored according to its time-dependent dynamics. Conclusion
The Voronoi-based approach used here enables the user to perform accurate
computations of the geometry of the internal cavities in biomolecules. For the
first time, it is possible to compute dynamic molecular paths that have a
user-defined minimum constriction size. To illustrate the usefulness of the
tool for understanding protein dynamics, we probe the dynamic structure of
internal cavities in the bacteriorhodopsin proton pump
Intrinsic shape analysis in archaeology: A case study on ancient sundials
This paper explores a novel mathematical approach to extract archaeological
insights from ensembles of similar artifact shapes. We show that by considering
all the shape information in a find collection, it is possible to identify
shape patterns that would be difficult to discern by considering the artifacts
individually or by classifying shapes into predefined archaeological types and
analyzing the associated distinguishing characteristics. Recently, series of
high-resolution digital representations of artifacts have become available, and
we explore their potential on a set of 3D models of ancient Greek and Roman
sundials, with the aim of providing alternatives to the traditional
archaeological method of ``trend extraction by ordination'' (typology). In the
proposed approach, each 3D shape is represented as a point in a shape space --
a high-dimensional, curved, non-Euclidean space. By performing regression in
shape space, we find that for Roman sundials, the bend of the sundials'
shadow-receiving surface changes with the location's latitude. This suggests
that, apart from the inscribed hour lines, also a sundial's shape was adjusted
to the place of installation. As an example of more advanced inference, we use
the identified trend to infer the latitude at which a sundial, whose
installation location is unknown, was placed. We also derive a novel method for
differentiated morphological trend assertion, building upon and extending the
theory of geometric statistics and shape analysis. Specifically, we present a
regression-based method for statistical normalization of shapes that serves as
a means of disentangling parameter-dependent effects (trends) and unexplained
variability.Comment: accepted for publication from the ACM Journal on Computing and
Cultural Heritag
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