A multimap is a generalization of the common map data structure, also known as a dictionary or associative array.
Such a method, instead of using a map data structure with a PSQ as pointer, uses a sequence [35] of tuples (creationtime, message-queue) with each sequence data structure being responsible for a specific destination of messages.
A map data structure named cumulativeLaxities is used to store the cumulative laxity for each execution phase, where the key is the execution phase and the value is the cumulative laxity.
The agents (cells) are stored via a multi-map data structure, which is indexed by location and stores pointers to agent properties.
Furthermore, we developed a novel map data structure to validate read alignments, a strategy to compare variants binned in size ranges and a lightweight, interactive, graphical report to visualize validation results with detailed statistics.
During vectorization, structural multimaps are first replaced by structural maps ordinary map data structures that map a structural path to a corresponding single numeric value.
From the point of view of data processing, we are clearly facing a problem of semantic mapping and data structuring.
The lesson from databases is that systems of systems need to be able to recognize automatically the information that is encoded in the different types of data and then reason about the different encoding to derive a mapping between data structures.
Because the Dengue 3′UTR is predicted to harbor multiple pseudoknot structures, we used the recently developed software program Shapeknots (Hajdin et al., 2013) to incorporate our chemical mapping data into secondary structure prediction algorithms capable of identifying such structures.
As mentioned above, GM maps and DBM maps have different data structure.
Mapping data suggested more structure variation (SV) in the B. juncea genome than in B. rapa.
