March 7, 2017

Outer-Art, Vol. II: the Worst Possible art in the World! by Florentin Smarandache

By Florentin Smarandache

OUTER-aRT is a circulation organize via Florentin Smarandachein 1990's (as a protest opposed to random smooth artwork, the place whatever may perhaps mean... art!) and is composed in making artwork as grotesque as attainable, as mistaken as attainable, or as foolish as attainable, and usually as very unlikely as attainable! it's an upside-down art!... to do artwork within the means it's not imagined to be done... Manifestos and anti-manifestos, essays, interviews, including a published oUTER-aRT Gallery are to be present in this (outer-)album of (outer-)painting, (outer-)drawings, (outer-)collages, (outer-)photos.

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Extra info for Outer-Art, Vol. II: the Worst Possible art in the World! (painting, drawings, collages, photos)

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5, many of the parcel centroids could not be properly referenced from the TIGER street centerlines and would be assigned to the incorrect Census Block based on a point-in-polygon search. The solution to this problem is to develop a comprehensive set of street centerlines at a scale that ensures that the location of lots, houses, and other buildings will be topologically correct. In the United Kingdom, the Ordinance Survey solved the problem by digitizing buildings and roads from large-scale map sources.

Often the results of these infield scouting efforts are single point locations or isolated polygon locations with random positioning and spacing. , 1996; Stehman, 2001). In addition, research is necessary to identify the optimum method of interpolating between point observations to derive a continuous statistical surface in one of several data structures, including: raster, triangular-irregular-network (TIN), quad-tree, etc. , inverse distance-weighting versus geostatistical kriging (Atkinson and Lewis, 2000; Davidson and Csillag, 2003).

1985). , 1998). , 1997). Tools for managing uncertainty in conflation systems currently under development include fuzzy logic, semantic constraints, expert systems, Dempster-Shafer theory, and Bayesian networks. The following subsections briefly identify several additional generic spatial data integration issues (quality, consistency, and comparability) that should be addressed before data are collected, including: standards, geoid and datum, positional accuracy, classification system (scheme), in situ sampling logic, census enumeration logic, metadata collection, address matching, and privacy issues.

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