Event-based processing of neutron scattering data

Computational Analysis of Neutron Scattering Data

This work explores potential methods for use in the detection and classification of defects within crystal structures via analysis of diffuse scattering data generated by single crystal neutron scattering experiments. The proposed defect detection methodology uses machine learning and image processing techniques to perform image texture analysis on neutron diffraction patterns generated by neut...

Simultaneous fitting of X-ray and neutron diffuse scattering data.

Conventional crystallographic refinement uses the Bragg-peak intensities and gives the single-site average crystal structure. Information about short-range order and local order is contained in the diffuse scattering that is distributed throughout reciprocal space. Models of the short-range order in materials can now be automatically refined. The complementarity of X-ray and neutron diffraction...

Resolution effects and analysis of small-angle neutron scattering data

Towards Ontology-Based Event Processing

The rapid change and heterogeneity of today’s generated data calls for real-time decision making systems that can cope with the presented heterogeneity. In this paper, we present an Ontology Based Event Processing system that bridges the gap between ontology-based reasoning and event processing. We propose both a language and an architecture to perform event processing over abstract ontology co...

Event-Based Statistical Signal Processing

In traditional time-based sampling, the sampling mechanism is triggered by predetermined sampling times, which are mostly uniformly spaced (i.e., periodic). Alternatively, in event-based sampling, some predefined events on the signal to be sampled trigger the sampling mechanism; that is, sampling times are determined by the signal and the event space. Such an alternative mechanism, setting the ...