Matching ontologies which utilize significantly heterogeneous terminologies is a challenging task for existing matching techniques. These techniques typically exploit lexical resources in order to enrich the ontologies with additional terminology such that more terminological matches can be found. However, they are limited by the availability of an appropriate lexical resource for each matching...

This paper describes a procedure developed at University College London for the automatic stereo matching of SAR imagery from NASA's Seasat satellite. The method employed uses Gruen's least squares correlation technique to improve the match accuracy of randomly generated points as they are cascaded down an image pyramid, coupled with a sheet growing mechanism in order to produce a dense array o...

A Service Level Agreement (SLA) is a business operations concept that is sometimes inappropriately applied to engineering development. When an SLA is not converted to engineering requirements, development occurs blindly and testing is probably done against some of the values specified in the SLA. The result is higher risk and higher cost. This paper illustrates some concepts concerning data com...

The rate flexibility and probabilistic shaping gain of 4-dimensional signaling is experimentally tested for short-reach, unrepeated transmission. A rate granularity of 0.5 bits/QAM symbol is achieved with a distribution matcher based on a simple look-up table. OCIS codes: 060.2330, 060.1660, 060.4080.

In this paper we give a brief explanation of how Sub-Ontology based Ontology Matching (SOBOM) method gets the alignment results at OAEI2010. SOBOM deal with an ontology from two different views: an ontology with is-a hierarchical structure O’ and an ontology with other relationships O’’. Firstly, from the O’ view, SOBOM starts with a set of anchors provided by a linguistic matcher. And then it ...

Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespr...

Graph matching is considered the recognition step in computer vision. Our work uses attributed relation graphs (ARG’s) for image representation and analysis, a structural description that we enhance with the complete and coherent spatial knowledge of the source image. In chapter 1 we reveal a trend where researchers are slowly incorporating more and more spatial knowledge into relational graphs...