29,723 research outputs found
Ontology based Scene Creation for the Development of Automated Vehicles
The introduction of automated vehicles without permanent human supervision
demands a functional system description, including functional system boundaries
and a comprehensive safety analysis. These inputs to the technical development
can be identified and analyzed by a scenario-based approach. Furthermore, to
establish an economical test and release process, a large number of scenarios
must be identified to obtain meaningful test results. Experts are doing well to
identify scenarios that are difficult to handle or unlikely to happen. However,
experts are unlikely to identify all scenarios possible based on the knowledge
they have on hand. Expert knowledge modeled for computer aided processing may
help for the purpose of providing a wide range of scenarios. This contribution
reviews ontologies as knowledge-based systems in the field of automated
vehicles, and proposes a generation of traffic scenes in natural language as a
basis for a scenario creation.Comment: Accepted at the 2018 IEEE Intelligent Vehicles Symposium, 8 pages, 10
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A Framework for Semi-automated Web Service Composition in Semantic Web
Number of web services available on Internet and its usage are increasing
very fast. In many cases, one service is not enough to complete the business
requirement; composition of web services is carried out. Autonomous composition
of web services to achieve new functionality is generating considerable
attention in semantic web domain. Development time and effort for new
applications can be reduced with service composition. Various approaches to
carry out automated composition of web services are discussed in literature.
Web service composition using ontologies is one of the effective approaches. In
this paper we demonstrate how the ontology based composition can be made faster
for each customer. We propose a framework to provide precomposed web services
to fulfil user requirements. We detail how ontology merging can be used for
composition which expedites the whole process. We discuss how framework
provides customer specific ontology merging and repository. We also elaborate
on how merging of ontologies is carried out.Comment: 6 pages, 9 figures; CUBE 2013 International Conferenc
P ORTOLAN: a Model-Driven Cartography Framework
Processing large amounts of data to extract useful information is an
essential task within companies. To help in this task, visualization techniques
have been commonly used due to their capacity to present data in synthesized
views, easier to understand and manage. However, achieving the right
visualization display for a data set is a complex cartography process that
involves several transformation steps to adapt the (domain) data to the
(visualization) data format expected by visualization tools. To maximize the
benefits of visualization we propose Portolan, a generic model-driven
cartography framework that facilitates the discovery of the data to visualize,
the specification of view definitions for that data and the transformations to
bridge the gap with the visualization tools. Our approach has been implemented
on top of the Eclipse EMF modeling framework and validated on three different
use cases
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