We use several diverse parameterizations of diffractive parton distributions, extracted in leading twist QCD analyses of the HERA diffractive deep inelastic scattering (DIS) data, to make predictions for leading twist nuclear shadowing of nuclear quark and gluon distributions in DIS on nuclei. We find that the HERA diffractive data are sufficiently precise to allow us to predict large nuclear s...

In this paper, we investigate automatic language proficiency assessment from learners’ utterances generated through shadowing and reading aloud. By increasing the degrees of difficulty of learners’ tasks for each practice, we examine how the automatic scores, the conventional GOP and proposed F-GOP, change according to the cognitive loads posed on learners. We also investigate the effect and si...

New synthetic aperture radar (SAR) sensors on satellites like TerrsSAR-X allow flexible mapping with a large coverage or a high resolution of about one meter. Leading-edge airborne SAR sensors provide spatial resolutions on the order of a decimetre. In such data, many features of urban objects can be identified, which were beyond the scope of radar remote sensing before. But, SAR images are oft...

Accurate vehicle positioning is important not only for in-car navigation systems but is also a requirement for emerging autonomous driving methods. Consumer level GPS are inaccurate in a number of driving environments such as in tunnels or areas where tall buildings cause satellite shadowing. Current vision-based methods typically rely on the integration of multiple sensors or fundamental matri...

This paper describes the land use classification of multispectral digital aerial images, the removal of buildings from the digital surface model and the visualization of the textured digital surface model with reconstructed buildings. The proposed approach applies spectral classification techniques to multispectral digital aerial images with RGB and NIR channels. The results of the land use cla...