168 research outputs found
Depicting urban boundaries from a mobility network of spatial interactions: A case study of Great Britain with geo-located Twitter data
Existing urban boundaries are usually defined by government agencies for
administrative, economic, and political purposes. Defining urban boundaries
that consider socio-economic relationships and citizen commute patterns is
important for many aspects of urban and regional planning. In this paper, we
describe a method to delineate urban boundaries based upon human interactions
with physical space inferred from social media. Specifically, we depicted the
urban boundaries of Great Britain using a mobility network of Twitter user
spatial interactions, which was inferred from over 69 million geo-located
tweets. We define the non-administrative anthropographic boundaries in a
hierarchical fashion based on different physical movement ranges of users
derived from the collective mobility patterns of Twitter users in Great
Britain. The results of strongly connected urban regions in the form of
communities in the network space yield geographically cohesive, non-overlapping
urban areas, which provide a clear delineation of the non-administrative
anthropographic urban boundaries of Great Britain. The method was applied to
both national (Great Britain) and municipal scales (the London metropolis).
While our results corresponded well with the administrative boundaries, many
unexpected and interesting boundaries were identified. Importantly, as the
depicted urban boundaries exhibited a strong instance of spatial proximity, we
employed a gravity model to understand the distance decay effects in shaping
the delineated urban boundaries. The model explains how geographical distances
found in the mobility patterns affect the interaction intensity among different
non-administrative anthropographic urban areas, which provides new insights
into human spatial interactions with urban space.Comment: 32 pages, 7 figures, International Journal of Geographic Information
Scienc
Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web
The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view. ii
Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web
The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view
Cooperative "folding transition" in the sequence space facilitates function-driven evolution of protein families
In the protein sequence space, natural proteins form clusters of families
which are characterized by their unique native folds whereas the great majority
of random polypeptides are neither clustered nor foldable to unique structures.
Since a given polypeptide can be either foldable or unfoldable, a kind of
"folding transition" is expected at the boundary of a protein family in the
sequence space. By Monte Carlo simulations of a statistical mechanical model of
protein sequence alignment that coherently incorporates both short-range and
long-range interactions as well as variable-length insertions to reproduce the
statistics of the multiple sequence alignment of a given protein family, we
demonstrate the existence of such transition between natural-like sequences and
random sequences in the sequence subspaces for 15 domain families of various
folds. The transition was found to be highly cooperative and two-state-like.
Furthermore, enforcing or suppressing consensus residues on a few of the
well-conserved sites enhanced or diminished, respectively, the natural-like
pattern formation over the entire sequence. In most families, the key sites
included ligand binding sites. These results suggest some selective pressure on
the key residues, such as ligand binding activity, may cooperatively facilitate
the emergence of a protein family during evolution. From a more practical
aspect, the present results highlight an essential role of long-range effects
in precisely defining protein families, which are absent in conventional
sequence models.Comment: 13 pages, 7 figures, 2 tables (a new subsection added
3DQ: Threat Dome Visibility Querying on Mobile Devices
3DQ (Three Dimensional Query) is our mobile spatial interaction (MSI) prototype for location and orientation aware mobile devices (i.e. today\u27s sensor enabled smartphones). The prototype tailors a military style threat dome query calculation using MSI with hidden query removal functionality for reducing “information overload” on these off-the-shelf devices. The effect gives a more accurate and expected query result for Location-Based Services (LBS) applications by returning information on only those objects visible within a user’s 3D field-of-view. Our standardised XML based request/response design enables any mobile device, regardless of operating system and/or programming language, to access the 3DQ web-service interfaces
Characterizing Human Mobility Patterns in a Large Street Network
Previous studies demonstrated empirically that human mobility exhibits Levy
flight behaviour. However, our knowledge of the mechanisms governing this Levy
flight behaviour remains limited. Here we analyze over 72 000 people's moving
trajectories, obtained from 50 taxicabs during a six-month period in a large
street network, and illustrate that the human mobility pattern, or the Levy
flight behaviour, is mainly attributed to the underlying street network. In
other words, the goal-directed nature of human movement has little effect on
the overall traffic distribution. We further simulate the mobility of a large
number of random walkers, and find that (1) the simulated random walkers can
reproduce the same human mobility pattern, and (2) the simulated mobility rate
of the random walkers correlates pretty well (an R square up to 0.87) with the
observed human mobility rate.Comment: 13 figures, 17 page
EgoViz – a Mobile Based Spatial Interaction System
This paper describes research carried out in the area of mobile spatial interaction and the development of a mobile (i.e. on-device) version of a simulated web-based 2D directional query processor. The TellMe application integrates location (from GPS, GSM, WiFi) and orientation (from digital compass/tilt sensors) sensing technologies into an enhanced spatial query processing module capable of exploiting a mobile device’s position and orientation for querying real-world 3D spatial datasets. This paper outlines the technique used to combine these technologies and the architecture needed to deploy them on a sensor enabled smartphone (i.e. Nokia 6210 Navigator). With all these sensor technologies now available on one device, it is possible to employ a personal query system that can work effectively in any environment using location and orientation as primary parameters for directional queries. In doing so, novel approaches for determining a user’s query space in 3 dimensions based on line-of-sight and 3D visibility (ego-visibility) are also investigated. The result is a mobile application that is location, direction and orientation aware and using these data is able to identify objects (e.g. buildings, points-of-interest, etc.) by pointing at them or when they are in a specified field-of-view
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