Icing climate representations proved beneficial for optimal designs and careful planning.
The representations prove to be well suited as a basis for path planning and navigation.
Although independently optimized multi-conformer representations prove to be a very attractive solution, interpretation of what the ensemble represents is a gray area [ 9, 12].
What the videos reveal about social exclusion, gender roles and the pernicious power of media representation proves these things are far from women-only issues.
It may be that some non-probabilistic representation proves more suitable than probability for modeling analogical reasoning.
This representation proves to be robust for syllable recognition under noise corruption.
However, there are situations in which the second order model representation proves to be inadequate and unrealistic due to the presence of lack of fit caused by third or higher order terms in the true response surface model.
This representation proved to be very effective in spoken language recognition [91] and other similar tasks [92].
The new operators based on a problem-specific representation proved to be more effective in terms of flexibility, complexity and transparency, and also in efficiency than the previous methods.
For these reasons, the bifactor representation proved to be more useful as a model for the structure of depression and anxiety symptoms in adolescents than the three factor model.
