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We use a real data fusion operation on population health, where the imputation of basic health risk factors is used to enrich a large-scale survey on self-reported health status.
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These Intrusion Detection templates are applied to the online (near real-time) data fusion operations in order to better assess possible threats.
Fig. 8 Directional data fusion process.
Data fusion is a technological operation undertaken for specific operational purposes, with the aim of gaining more information about specific queries of interest from the existing data.
Yet there is no compelling clinical data showing that the fusion operation works better than simple disc excision.
During the network operation, data fusion should be considered to eliminate unnecessary communications since the massively deployed sensor nodes generate a huge amount of redundant data, which makes it critical to collect only the valuable data.
In WSNs, the basic operation is data fusion, where data from multiple sensors are integrated together to form a single meaningful result [1].
To provide this additional information, a map fusion operation is performed.
This paper describes a multi-agent system to assure the operation efficiency and reliability in data fusion and management of a set of networked distributive sensors (NDS).
Data fusion, also known as statistical matching, is a technological operation whose aim is to integrate the information of two independent data sources.
Mobile agents can perform fusion operation over the large volume of imagery data at each sensor node in the target region.
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