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These methodologies are supported by models or algorithms able to infer the system behaviour upon changes in the experimental factors.
Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.
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The main advantages of the proposed methodology are supported by the use of a systematic approach to identify, score and weight guideline topics selection, limiting or exposing the influence of personal biases.
Development of the methodology was supported by the Newton Fund.
The methodology is supported by the concept of fuzzy system.
The formalization methodology is supported by a graphical software tool.
The methodology is supported by a social context analysis and highly participative design process.
Our methodology is supported by a case tool facilitating the tasks of data warehouse designers.
This methodology is supported by a set of theorems, whose proofs are presented in this paper.
This methodology is supported by four examples of the rigorous development of empirical correlations that may be of interest to minerals processing engineers.
The proposed methodology is supported by a new educational simulation tool, namely WiFiSim, aimed at the generic study of IEEE 802.11-based WLANs in a disciplined way.
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