Such statistical descriptors are involved in assessment of correlations between the microstructural components and are parts of mechanical theories which require formalization of the information about microstructural morphology.
This process does not require formalization through the courts.
A wide class of problems in science and engineering requires mathematical formalization.
For actual clustering tasks, the informal notion of intra-cluster density vs. inter-cluster sparsity requires amathematical formalization.
One hypothesis derived from our study is that the optimal level of formalization is a function of team size and that larger teams may require greater formalization.
To achieve this required the formalization of grammatical structures, the conventionalization of meanings of terms, and the invention of standard punctuation.
However, it will likely require greater formalization given the more quantitative nature, and sheer volume, of MPS data.
This strategy may require high formalization of interactions between providers and may be viewed as difficult to operationalize in a context where providers have varying schedules and high caseloads.
On the other hand, the use of formalisms which do not require hard formalizations of expert knowledge (such as to transform them into probability distributions or algebraic equations) permits to eliminate one of the strongest limitations of classical knowledge-based methods and other prior knowledge based methods (such as bayessian methods or structural equations).
In this paper, we propose an approach for semantic DW traceability that requires: (i) the formalization of each design phase, (ii) the identification of horizontal and vertical interactions (inside and between phases), (iii) their semantic definition, storage and usage.
While the mechanistic approach requires strict process formalization, emphasizes technical details, and constrains the modeling task to technology experts, the humanistic approach is more centered on the end-user.
