Multi-INT Query Language for DDDAS Designs

Abstract Context understanding is established from coordination of content, analysis, and interaction between users and machines. In this manuscript, a live-video computing (LVC) approach is presented for access to data, comprehension of context, and analysis for context assessment. Context assessment includes multimedia fusion of query-based text, images, and exploited tracks, which are utilized for information retrieval. We explore developments in database systems which enable context to be extracted by user-based queries. Using a common image processing data set, we demonstrate activity analysis with context, privacy, and semantic-awareness in a Dynamic Data-Driven Applications System (DDDAS).

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