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Uncertainties due to natural randomness or aleatory uncertainties may be taken into account by using the stochastic or fuzzy methodologies, which enable us to quantify uncertainties.
Consequently, the demand for novel methodologies, which enable scale-correlated analysis, increases in order to describe a hierarchy of multi-scale systems in various length and time scales.
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The analysis of such constraints provides a schedule design methodology which enables a scalable solution.
It is therefore desirable to develop a methodology which enables the quick and easy measurement of geometry, damage and predictions of strength and stiffness.
By studying the fundamental constraints given by the considered measurement model, we provide a system design methodology which enables a scalable solution.
A new fatigue life evaluation methodology, which enables to predict fatigue crack growth from a stress concentration site without the initial defect is proposed.
The work offers a new learning mechanism, namely the "Learn-On-Demand" (LOD) methodology, which enables the ANN to learn where the lack of knowledge is evident.
This paper presents a methodology which enables a human operator to precisely control the motion of a multi-DOF piezo-actuated flexure mechanism with haptic feedback.
The aim of this paper is to introduce an urban planning methodology which enables planners to select projects, which fit the main goal of the city and develop a resilient strategy structure, based on the selected projects.
In order to reduce it, we have developed an original methodology which enables risk assessments to be carried out in fully quantitative terms, integrating both physical and economic science techniques.
The approach is supported by an error-evaluation methodology which enables the comparison of the model of the component and the form generated by FE simulation and form-measurement.
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