125,566 research outputs found
All mixed up? Finding the optimal feature set for general readability prediction and its application to English and Dutch
Readability research has a long and rich tradition, but there has been too little focus on general readability prediction without targeting a specific audience or text genre. Moreover, though NLP-inspired research has focused on adding more complex readability features there is still no consensus on which features contribute most to the prediction. In this article, we investigate in close detail the feasibility of constructing a readability prediction system for English and Dutch generic text using supervised machine learning. Based on readability assessments by both experts
and a crowd, we implement different types of text characteristics ranging from easy-to-compute superficial text characteristics to features requiring a deep linguistic processing, resulting in ten
different feature groups. Both a regression and classification setup are investigated reflecting the two possible readability prediction tasks: scoring individual texts or comparing two texts. We show that going beyond correlation calculations for readability optimization using a wrapper-based genetic algorithm optimization approach is a promising task which provides considerable insights in which feature combinations contribute to the overall readability prediction. Since we also have gold standard information available for those features requiring deep processing we are able to investigate the true upper bound of our Dutch system. Interestingly, we will observe that the performance of our fully-automatic readability prediction pipeline is on par with the pipeline using golden deep syntactic and semantic information
The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries
Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups
The Maunakea Spectroscopic Explorer Book 2018
(Abridged) This is the Maunakea Spectroscopic Explorer 2018 book. It is
intended as a concise reference guide to all aspects of the scientific and
technical design of MSE, for the international astronomy and engineering
communities, and related agencies. The current version is a status report of
MSE's science goals and their practical implementation, following the System
Conceptual Design Review, held in January 2018. MSE is a planned 10-m class,
wide-field, optical and near-infrared facility, designed to enable
transformative science, while filling a critical missing gap in the emerging
international network of large-scale astronomical facilities. MSE is completely
dedicated to multi-object spectroscopy of samples of between thousands and
millions of astrophysical objects. It will lead the world in this arena, due to
its unique design capabilities: it will boast a large (11.25 m) aperture and
wide (1.52 sq. degree) field of view; it will have the capabilities to observe
at a wide range of spectral resolutions, from R2500 to R40,000, with massive
multiplexing (4332 spectra per exposure, with all spectral resolutions
available at all times), and an on-target observing efficiency of more than
80%. MSE will unveil the composition and dynamics of the faint Universe and is
designed to excel at precision studies of faint astrophysical phenomena. It
will also provide critical follow-up for multi-wavelength imaging surveys, such
as those of the Large Synoptic Survey Telescope, Gaia, Euclid, the Wide Field
Infrared Survey Telescope, the Square Kilometre Array, and the Next Generation
Very Large Array.Comment: 5 chapters, 160 pages, 107 figure
Current Performance and On-Going Improvements of the 8.2 m Subaru Telescope
An overview of the current status of the 8.2 m Subaru Telescope constructed
and operated at Mauna Kea, Hawaii, by the National Astronomical Observatory of
Japan is presented. The basic design concept and the verified performance of
the telescope system are described. Also given are the status of the instrument
package offered to the astronomical community, the status of operation, and
some of the future plans. The status of the telescope reported in a number of
SPIE papers as of the summer of 2002 are incorporated with some updates
included as of 2004 February. However, readers are encouraged to check the most
updated status of the telescope through the home page,
http://subarutelescope.org/index.html, and/or the direct contact with the
observatory staff.Comment: 18 pages (17 pages in published version), 29 figures (GIF format),
This is the version before the galley proo
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