The Babylonians, Sumerians, Greeks, Chinese, Indians and Persians all had slightly different ways of quantifying objects and areas and slightly different ways of writing down their numbers.
We observed high correlation between manual and automated measurements for all wing traits (RWL = 0.98, RWW = 0.95, RWA = 0.99) and slightly lower correlation for the two body traits (RIOD = 0.83, RSW = 0.93), which may reflect the difficulty of quantifying 3D objects accurately from 2D projections.
Many theorists assume that the logical forms of such sentences should be tripartite structures with a quantifier that quantifies over objects or situations, a restrictor that limits the quantificational domain, and a nuclear scope (main clause) that makes an assertion about the elements of the domain (e.g., see Carlson 2011; Cohen 2002; or Carlson & Pelletier 1995).
The use of the ALiDAR data together with L-Architect allowed quantifying how significant object occlusion affects untreated data.
Modern laboratories use a vast number of instruments and procedures to study, systematize, or quantify the objects of their attention.
After all, we often quantify over objects we have no reason to believe exist, such as fictional entities.
After all, we can quantify over objects that do not exist, given the rejection of the indispensability argument's first premise.
Nevertheless, the comparison of the results with an urban database realized using a Computer Assisted Photo-Interpretation method shows a better capacity to delineate urban extent at regional scale and to quantify urban objects at local scale.
Additionally, the contributions of diverse semantic layers are quantified: the object-category layer is the most important and makes 54% contribution to functional-zone classification; while, other semantic layers are less important but their contributions cannot be ignored.
Objects were quantified using an automated object count function from this thresholded region and exported to Excel (Microsoft).
