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The widespread use of location-aware devices together with the increased popularity of micro-blogging applications (e.g., Twitter) led to the creation of large streams of spatio-textual data. In order to serve real-time applications, the processing of these large-scale spatio-textual streams needs to be distributed. However, existing distributed stream(More)
The ubiquity of location-aware devices, e.g., smartphones and GPS devices, has led to a plethora of location-based services in which huge amounts of geotagged information need to be efficiently processed by large-scale computing clusters. This demo presents AQWA, an adaptive and query-workload-aware data partitioning mechanism for processing large-scale(More)
OBJECTIVE To assess maternal serum amyloid A (SAA) levels among women with primary unexplained recurrent early pregnancy loss (REPL). METHODS A prospective study was conducted among women with missed spontaneous abortion in the first trimester at Ain Shams University Maternity Hospital, Cairo, Egypt, between January 21 and December 25, 2014. Women with at(More)
Advances in location-based services (LBS) demand high-throughput processing of both static and streaming data. Recently, many systems have been introduced to support distributed main-memory processing to maximize the query throughput. However, these systems are not optimized for spatial data processing. In this demonstration, we showcase Cruncher, a(More)
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