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Accurate and realistic movements of virtual components can be obtained based on constraints analysis, determination of resultant forces from contacts with real components and manipulation from the user's hands (forces and torques applied, etc).
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A new approach based on constraint analysis is conducted to determine the magnitudes of tension.
A hybrid method based on constraint analysis is presented, which interprets users' manual assembly intents robustly without the need for auxiliary CAD information.
On the other hand, large quantities of in silico optimization methods have been developed and both gene-level and reaction-level strategies can be identified based on constraint-based flux analysis.
The analysis is used to determine optimum stack designs based on constraints on desired performance and overall stack size.
Explanations based on constraints begin by demonstrating mutation rates, path-dependence, or other constraints that limit optimality.
We build a data-flow analysis based on constraint graphs, whose nodes are program points and whose arcs propagate information according to the semantics of each bytecode instruction.
They both are based on constraint solving.
RNAiFold, in contrast, is based on constraint programming techniques, which produce only solutions that completely comply with all given constraints.
We propose to adapt an approach to solve this problem based on interval analysis, constraint propagation and model reformulation.
In this paper for the preliminary stage, the feasible sequences of operations are generated based on the analysis of constraints and using a genetic algorithm (GA).
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