This involves an end-use validation, for which we designed a test to evaluate (i) the end-use value of the selected indicators as decision aid tools, (ii) the end-use value of MOTIFS as a decision aid tool and communication tool and (iii) the willingness of potential end-users to use MOTIFS in practice.
In this case, the synthetic index expresses the level of performance of the different selected indicators as respect to the criterion referring to each analyzed experiences, and make them explicit in the 'information matrix'.
To address this issue, we selected indicators that were as objective as possible and used a generic framework proposed by the United States CDC for FETPs.
Nevertheless, this data can be analysed using appropriate cloud based processing infrastructures to indicate statistical correlations about various indicators e.g. health, employment and citizen perception about selected indicators such as quality of life, as demonstrated in Section "Prototype implementation".
The selected indicators, such as tensile failure strain, validated that significant linear correlations existed between bending beam test and thermal stress restrained specimens test.
This is independent of selected indicators such as women's employment, education level and household location.
However, in our study, comparison of selected indicators such as of demographic data, health status data, utilization of health care services and risk factors between Queensland and Australia did not sustain this as an explanation (Table 1).
Selection of target values for selected indicators: after having selected a set of indicators as explained before, it is necessary to set favored target values.
Nine selected indicators are then assessed as good (3), fair (2), or poor (1).
Second, a multinomial logistic regression analysis is performed with type of union status (single, LAT, cohabiting, married) as the dependent variable, and the selected indicators of correlates and precursors as independent variables.
The selected indicators are hereafter referred to as the input parameters of a FIS, which are aggregated to obtain an indicator known as FCI.
