Tiled Projector Displays Correction for Dark Scenes in Railway Simulators

Tiled projector displays are a common choice for training simulators, where a high resolution output image is required. They are cheap for the resolution that they can reach and can be configured in many different ways. Nevertheless, such kinds of displays require geometric and color correction so that the composite image looks seamless. Display correction is an even bigger challenge when the projected images include dark scenes combined with brighter scenes. This is usually a problem for railway simulators when the train is positioned inside a tunnel and the black offset effect becomes noticeable. In this paper, a method for fast photometric and geometric correction of tiled display systems where dark and bright scenes are combined is presented. The image correction is carried out in two steps. First, geometric alignment and overlapping areas attenuation for brighter scenes is applied. Second, in the event of being inside a tunnel, the brightness of the scene is increased in certain areas using light sources in order to create the impression of darkness but minimizing the effect of the black offset

morph-LDP: an R2RML-based Linked Data Platform implementation

The W3C Linked Data Platform (LDP) candidate recom- mendation defines a standard HTTP-based protocol for read/write Linked Data. The W3C R2RML recommendation defines a language to map re- lational databases (RDBs) and RDF. This paper presents morph-LDP, a novel system that combines these two W3C standardization initiatives to expose relational data as read/write Linked Data for LDP-aware ap- plications, whilst allowing legacy applications to continue using their relational databases.

Formalisation and experiences of R2RML-based SPARQL to SQL query translation using Morph

R2RML is used to specify transformations of data available in relational databases into materialised or virtual RDF datasets. SPARQL queries evaluated against virtual datasets are translated into SQL queries according to the R2RML mappings, so that they can be evaluated over the underlying relational database engines. In this paper we describe an extension of a well-known algorithm for SPARQL to SQL translation, originally formalised for RDBMS-backed triple stores, that takes into account R2RML mappings. We present the result of our implementation using queries from a synthetic benchmark and from three real use cases, and show that SPARQL queries can be in general evaluated as fast as the SQL queries that would have been generated by SQL experts if no R2RML mappings had been used.