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MOOSE (Multiphysics Object Oriented Simulation Environment) is an object-oriented C++ finite element framework for the development of tightly coupled multiphysics solvers from Idaho National Laboratory. [1] MOOSE makes use of the PETSc non-linear solver package and libmesh to provide the finite element discretization.
The knobcone pine, Pinus attenuata (also called Pinus tuberculata), [2] is a tree that grows in mild climates on poor soils. It ranges from the mountains of southern Oregon to Baja California with the greatest concentration in northern California and the Oregon-California border.
The Pinaceae (/ p ɪ ˈ n eɪ s iː ˌ iː,-s i ˌ aɪ /), or pine family, are conifer trees or shrubs, including many of the well-known conifers of commercial importance such as cedars, firs, hemlocks, piñons, larches, pines and spruces.
OR-Tools was created by Laurent Perron in 2011. [5]In 2014, Google's open source linear programming solver, GLOP, was released as part of OR-Tools. [1]The CP-SAT solver [6] bundled with OR-Tools has been consistently winning gold medals in the MiniZinc Challenge, [7] an international constraint programming competition.
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner.
Pitch pine is known to cross with pond loblolly and shortleaf pines. One of those crosses is the pitlolly pine (pinus x rigitaeda), a natural hybrid between the loblolly pine and the pitch pine. This hybrid combines the tall size of the loblolly pine and the cold-hardiness of the pitch pine. This hybrid was used as substitute of loblolly pine ...
Stone pine in Brissago, on Lake Maggiore, Switzerland. The stone pine is a coniferous evergreen tree that can exceed 25 metres (80 feet) in height, but 12–20 m (40–65 ft) is more typical.
The Hierarchical navigable small world (HNSW) algorithm is a graph-based approximate nearest neighbor search technique used in many vector databases. [1] [2] Nearest neighbor search without an index involves computing the distance from the query to each point in the database, which for large datasets is computationally prohibitive.