E-Assessment Data Compatibility Resolution Methodology with Bidirectional Data Transformation

Methodology for Assessment of Linked Data Quality

With the expansion in the amount of data being produced as Linked Data (LD), the opportunity to build use cases has also increased. However, a crippling problem to the reliability of these use cases is the underlying poor data quality. Moreover, the ability to assess the quality of the consumed LD, based on the satisfaction of the consumers’ quality requirements, significantly influences usabil...

Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment

The availability of water surface inundation with high spatial resolution is of fundamental importance in several applications such as hydrology, meteorology and ecology. Medium spatial resolution sensors, like MODerate-resolution Imaging Spectroradiometer (MODIS), exhibit a significant potential to study inundation dynamics over large areas because of their high temporal resolution. However, t...

Bidirectional discrimination with application to data visualization.

Linear classifiers are very popular, but can have limitations when classes have distinct subpopulations. General nonlinear kernel classifiers are very flexible, but do not give clear interpretations and may not be efficient in high dimensions. We propose the bidirectional discrimination classification method, which generalizes linear classifiers to two or more hyperplanes. This new family of cl...

Methodology for Clustering High-Resolution Spatiotemporal Solar Resource Data

Compatibility of SAS Data Library

This paper presents an overview of backwards and forwards compatibility between Versions 6 and 7 of the SAS System and is intended to be used as a reference in determining what manner of access is allowed. Furthermore, this paper takes into account differences in compatibility between the Base SAS System and when products such as SAS/CONNECT and SAS/SHARE are used. SAS I/O Services The I/O Se...