Abstract:
A method, apparatus, and system is described for creating a spatial sieve tree which stores, manages, and manipulates multidimensional data by partitioning the bounds of the nodes of the tree, creating child nodes which each have defined bounds associated with a partitioned portion of their parent node(s) and may be further partitioned into additional levels of child nodes, and determining which level of the tree has the smallest size node in which a data object could wholly fit regardless of the data object's location in coordinate space and the one or more nodes of that determined level that could at least partially contain the data object based on the bounds of the one or more nodes and the data object's location in coordinate space.
Abstract:
Various embodiments include an apparatus comprising a detection database including a tree structure of descriptor parts including one or more root nodes and one or more child nodes linked to from one or more parent descriptor parts chains, each of the root nodes representing a descriptor part, and each root node linked to at least one of the child nodes, each root node and each child node linked to any possible additional child nodes, wherein the possible additional child nodes include any possible successor child nodes and a descriptor comparator coupled to the detection database, the descriptor comparator operable to receive data including a plurality of logic entities, once or successively, and to continuously compare logic entities provided to the tree structure of descriptor parts stored in detection database, and to provide an output based on the comparison.
Abstract:
An octree GPU construction system and method for constructing a complete octree data structure on a graphics processing unit (GPU). Embodiments of the octree GPU construction system and method first defines a complete octree data structure as forming a complete partition of the 3-D space and including a vertex, edge, face, and node arrays, and neighborhood information. Embodiments of the octree GPU construction system and method input a point cloud and construct a node array. Next, neighboring nodes are computed for each of the nodes in the node arrays by using at least two pre-computed look-up tables (such as a parent look-up table and a child look-up table). Embodiments of the octree GPU construction system and method then use the neighboring nodes and neighborhood information to compute a vertex array, edge array, and face array are computed by determining owner information and self-ownership information based on the neighboring nodes.
Abstract:
Multiple sets of data are obtained from different sources. Each data set is represented using a different format having a different syntax and organized in a multi-level nested data structure. Each data set is reformatted into a standardized table format using a depth-first recursive algorithm without relying on the syntax schema of the original format of the data set. Various operations are performed on the tables corresponding to the data sets, including but not limited to joining multiple tables, grouping selected rows of a table, ranking rows of a table, adding or deleting fields from selected rows of a table, etc. Optionally, inferred namespace and text normalization are utilized for selected table operations. One or more templates are provided for converting the data set of a table to a format that may be presented to a user.
Abstract:
A group identifier represents an association between each of a number of different abbreviated namespace identifiers with a corresponding hierarchical namespace (e.g., an XML namespace). A hierarchically-structured document (e.g., an XML document) is accessed by a computing system that determines that the group identifier is associated with the hierarchically-structured document. Hence, when using the abbreviated namespace identifiers in the hierarchically-structured document, the computing system knows that the corresponding namespace is associated with the designated portions of the hierarchically-structured document. Also, a schema description language document (e.g., an XSD document) may specify multiple target namespaces for a single element. Accordingly, groupings of elements may be included in different namespaces to creating overlapping or even nested namespaces.
Abstract:
A pipelined search engine device, such as a longest prefix match (LPM) search engine device, includes a hierarchical memory and a pipelined tree maintenance engine therein. The hierarchical memory is configured to store a b−tree of search prefixes (and possibly span prefix masks) at multiple levels therein. The pipelined tree maintenance engine, which is embedded within the search engine device, includes a plurality of node maintenance sub-engines that are distributed with the multiple levels of the hierarchical memory. The search engine device may also include pipeline control and search logic that is distributed with the multiple levels of the hierarchical memory.
Abstract:
A system and method to visually navigate hierarchical data groups are provided. If a user wishes to graphically view network traffic data for a particular business group of network nodes, a network topology navigation tool may be provided to display to the user such information that is relevant to the selected business group and the corresponding hierarchy level. The user may also be permitted to access more detailed connection information through appropriate drill-downs.
Abstract:
Disclosed is a method of encoding a tree structure and associated methods of traversing, manipulating and querying the tree. As tree structures are widely used in the field of computer science (as document formats like XML, as object trees of object-oriented programming languages, as XML and object databases etc), genetic analysis and other fields of science, the methods disclosed in this invention will be advantageous in analysing and indexing tree structures. Other embodiments are also disclosed.
Abstract:
A method, apparatus, and system is described for creating a spatial sieve tree which stores, manages, and manipulates multidimensional data by partitioning the bounds of the nodes of the tree, creating child nodes which each have defined bounds associated with a partitioned portion of their parent node(s) and may be further partitioned into additional levels of child nodes, and determining which level of the tree has the smallest size node in which a data object could wholly fit regardless of the data object's location in coordinate space and the one or more nodes of that determined level that could at least partially contain the data object based on the bounds of the one or more nodes and the data object's location in coordinate space.