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To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR.
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First, to identify activity related to the simultaneous processing of visual and kinesthetic information (visuokinesthetic processing), we defined a linear contrast of [(CONG + INCONG) vs. (F B + E B)] (main effect of visuokinesthetic processing in a 2 × 2 factorial design).
Moreover, to simplify the operation of event processing, we defined a common execution interface for all of event types.
After default raw data processing, we used a resequencing trimming filter to increase the data output.
Using a commercial graphics processing unit that has been optimized for parallel data processing, we report a complete high-speed SS-OCT platform capable of real-time data acquisition, processing, display, and saving at 108,000 lines per second.
We defined a total of 14 lots.
Moreover, to provide the security for the in-networking processing such as data aggregation in WSANs, we define a multiple-key management scheme in conjunction with our proposed Ripple-Zone routing architecture.
For comparison with the recommended process noise values for the tropospheric parameters suggested by Bar-Sever et al. (1998), we defined an elevation cutoff angle of 7° during data processing.
In this work, we define a custom data processing pipeline for Pacific Biosciences data for human data analysis.
We define a simple method to detect cortical states that can be applied in real time for offline processing of large amounts of recorded data on conventional computers.
To begin, we consider data sharing as a form of data processing as defined by the EU Directive 95/46/EC on data protection [ 7].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com