Despite their strengths, object-oriented metho ds (OOMs) and their supporting CASE to ols often do not produce models that are amenable to rigor ous semantic analysis. This is a direct result of their loosely de ned semantics. In this paper we outline our ongoing work on providing a semantic b ase for OOMs.

Understanding growth patterns at the metropolitan level is instructive for better planning and policy making on sustainable urban development. Using DMSP/OLS data from 1992 to 2013, this article aims to investigate growth patterns of major metropolitans in Mainland China from the aspects of intensification and expansion. We start by calibrating the DMSP/OLS data and selecting 45 major metropoli...

Linear regression is one of the most prevalent techniques in machine learning; however, it is also common to use linear regression for its explanatory capabilities rather than label prediction. Ordinary Least Squares (OLS) is often used in statistics to establish a correlation between an attribute (e.g. gender) and a label (e.g. income) in the presence of other (potentially correlated) features...