Applications in many domains require processing moving object trajectories. In this work, we focus on a trajectory similarity search that finds all trajectories within a given distance of a query trajectory over a time interval, which we call the dis
tance threshold similarity search. We develop three indexing strategies with spatial, temporal and spatiotemporal selectivity for the GPU that differ significantly from indexes suitable for the CPU, and show the conditions under which each index achieves good performance. Furthermore, we show that the GPU implementations outperform multithreaded CPU implementations in a range of experimental scenarios, making the GPU an attractive technology for processing moving object trajectories. We test our implementations on two synthetic and one real-world dataset of a galaxy merger.
In this study, we combine bibliometric techniques with a machine learning algorithm, the sequential Information Bottleneck, to assess the interdisciplinarity of research produced by the University of Hawaii NASA Astrobiology Institute (UHNAI). In par
ticular, we cluster abstract data to evaluate Thomson Reuters Web of Knowledge subject categories as descriptive labels for astrobiology documents, assess individual researcher interdisciplinarity, and determine where collaboration opportunities might occur. We find that the majority of the UHNAI team is engaged in interdisciplinary research, and suggest that our method could be applied to additional NASA Astrobiology Institute teams in particular, or other interdisciplinary research teams more broadly, to identify and facilitate collaboration opportunities.
We present a model of the Galactic Habitable Zone (GHZ), described in terms of the spatial and temporal dimensions of the Galaxy that may favour the development of complex life. The Milky Way galaxy is modelled using a computational approach by popul
ating stars and their planetary systems on an individual basis using Monte-Carlo methods. We begin with well-established properties of the disk of the Milky Way, such as the stellar number density distribution, the initial mass function, the star formation history, and the metallicity gradient as a function of radial position and time. We vary some of these properties, creating four models to test the sensitivity of our assumptions. To assess habitability on the Galactic scale, we model supernova rates, planet formation, and the time required for complex life to evolve. Our study improves on other literature on the GHZ by populating stars on an individual basis and by modelling SNII and SNIa sterilizations by selecting their progenitors from within this preexisting stellar population. Furthermore, we consider habitability on tidally locked and non-tidally locked planets separately, and study habitability as a function of height above and below the Galactic midplane. In the model that most accurately reproduces the properties of the Galaxy, the results indicate that an individual SNIa is ~5.6 times more lethal than an individual SNII on average. In addition, we predict that ~1.2% of all stars host a planet that may have been capable of supporting complex life at some point in the history of the Galaxy. Of those stars with a habitable planet, ~75% of planets are predicted to be in a tidally locked configuration with their host star. The majority of these planets that may support complex life are found towards the inner Galaxy, distributed within, and significantly above and below, the Galactic midplane.
