1,280 research outputs found
ERDS: Emerging Risks Detection Support : 2007 project report
Rapport over het detecteren van risico's met de veiligheid van voeding. Aan de hand van het melamineschandaal wordt gekeken hoe in een vroegtijdig stadium risico's onderkend kunnen worde
Applying semantic web technologies to knowledge sharing in aerospace engineering
This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale
Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams
Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems
(CPS) present novel challenges to Big Data platforms for performing online
analytics. Ubiquitous sensors from IoT deployments are able to generate data
streams at high velocity, that include information from a variety of domains,
and accumulate to large volumes on disk. Complex Event Processing (CEP) is
recognized as an important real-time computing paradigm for analyzing
continuous data streams. However, existing work on CEP is largely limited to
relational query processing, exposing two distinctive gaps for query
specification and execution: (1) infusing the relational query model with
higher level knowledge semantics, and (2) seamless query evaluation across
temporal spaces that span past, present and future events. These allow
accessible analytics over data streams having properties from different
disciplines, and help span the velocity (real-time) and volume (persistent)
dimensions. In this article, we introduce a Knowledge-infused CEP (X-CEP)
framework that provides domain-aware knowledge query constructs along with
temporal operators that allow end-to-end queries to span across real-time and
persistent streams. We translate this query model to efficient query execution
over online and offline data streams, proposing several optimizations to
mitigate the overheads introduced by evaluating semantic predicates and in
accessing high-volume historic data streams. The proposed X-CEP query model and
execution approaches are implemented in our prototype semantic CEP engine,
SCEPter. We validate our query model using domain-aware CEP queries from a
real-world Smart Power Grid application, and experimentally analyze the
benefits of our optimizations for executing these queries, using event streams
from a campus-microgrid IoT deployment.Comment: 34 pages, 16 figures, accepted in Future Generation Computer Systems,
October 27, 201
Scalable software framework for real-time data processing in the railway environment
Background: Ticks are obligate haematophagous ectoparasites of vertebrates and frequently parasitize avian species that can carry them across continents during their long-distance migrations. Ticks may have detrimental effects on the health state of their avian hosts, which can be either directly caused by blood-draining or mediated by microbial pathogens transmitted during the blood meal. Indeed, ticks host complex microbial communities, including bacterial pathogens and symbionts. Midichloria bacteria (Rickettsiales) are widespread tick endosymbionts that can be transmitted to vertebrate hosts during the tick bite, inducing an antibody response. Their actual role as infectious/pathogenic agents is, however, unclear. Methods: We screened for Midichloria DNA African ticks and blood samples collected from trans-Saharan migratory songbirds at their arrival in Europe during spring migration. Results: Tick infestation rate was 5.7%, with most ticks belonging to the Hyalomma marginatum species complex. Over 90% of Hyalomma ticks harboured DNA of Midichloria bacteria belonging to the monophylum associated with ticks. Midichloria DNA was detected in 43% of blood samples of avian hosts. Tick-infested adult birds were significantly more likely to test positive to the presence of Midichloria DNA than non-infested adults and second-year individuals, suggesting a long-term persistence of these bacteria within avian hosts. Tick parasitism was associated with a significantly delayed timing of spring migration of avian hosts but had no significant effects on body condition, whereas blood Midichloria DNA presence negatively affected fat deposits of tick-infested avian hosts. Conclusions: Our results show that ticks effectively transfer Midichloria bacteria to avian hosts, supporting the hypothesis that they are infectious to vertebrates. Bird infection likely enhances the horizontal spread of these bacteria across haematophagous ectoparasite populations. Moreover, we showed that Midichloria and tick parasitism have detrimental non-independent effects on avian host health during migration, highlighting the complexity of interactions involving ticks, their vertebrate hosts, and tick-borne bacteria
A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases
PhDData stored in individual autonomous databases often needs to be combined and
interrelated. For example, in the Inland Water (IW) environment monitoring domain,
the spatial and temporal variation of measurements of different water quality indicators
stored in different databases are of interest. Data from multiple data sources is more
complex to combine when there is a lack of metadata in a computation forin and when
the syntax and semantics of the stored data models are heterogeneous. The main types
of information retrieval (IR) requirements are query transparency and data
harmonisation for data interoperability and support for multiple user views. A
combined Semantic Web based and Agent based distributed system framework has
been developed to support the above IR requirements. It has been implemented using
the Jena ontology and JADE agent toolkits. The semantic part supports the
interoperability of autonomous data sources by merging their intensional data, using a
Global-As-View or GAV approach, into a global semantic model, represented in
DAML+OIL and in OWL. This is used to mediate between different local database
views. The agent part provides the semantic services to import, align and parse
semantic metadata instances, to support data mediation and to reason about data
mappings during alignment. The framework has applied to support information
retrieval, interoperability and multi-lateral viewpoints for four European environmental
agency databases.
An extended GAV approach has been developed and applied to handle queries that can
be reformulated over multiple user views of the stored data. This allows users to
retrieve data in a conceptualisation that is better suited to them rather than to have to
understand the entire detailed global view conceptualisation. User viewpoints are
derived from the global ontology or existing viewpoints of it. This has the advantage
that it reduces the number of potential conceptualisations and their associated
mappings to be more computationally manageable. Whereas an ad hoc framework
based upon conventional distributed programming language and a rule framework
could be used to support user views and adaptation to user views, a more formal
framework has the benefit in that it can support reasoning about the consistency,
equivalence, containment and conflict resolution when traversing data models. A
preliminary formulation of the formal model has been undertaken and is based upon
extending a Datalog type algebra with hierarchical, attribute and instance value
operators. These operators can be applied to support compositional mapping and
consistency checking of data views. The multiple viewpoint system was implemented
as a Java-based application consisting of two sub-systems, one for viewpoint
adaptation and management, the other for query processing and query result
adjustment
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