Dimensionality reduction and feature subset selection are two techniques for reducing the attribute space of a feature set, which is an important component of both supervised and unsupervised classification or regression problems. While in feature subset selection a subset of the original attributes is extracted, dimensionality reduction in general produces… (More)
This paper emphasizes the importance of Data Mining classification algorithms in predicting the vehicle collision patterns occurred in training accident data set.
The objective of this study was to investigate depth perception in astronauts during and after spaceflight by studying their sensitivity to reversible perspective figures in which two-dimensional images could elicit two possible depth representations. Other ambiguous figures that did not give rise to a perception of illusory depth were used as controls. Six… (More)
This experiment investigated whether the perception of depth-reversible figures is altered when the observer is in microgravity or hypergravity. A set of five bi-stable ambiguous figures was presented to ten participants in 1g, 0 g, and 1.8 g during parabolic flight. The figures included static images such as the Necker cube; kinetic depth displays such as… (More)