The dataset contains 61 dimensions describing clinical parameters such as sex, age, anthropometric measures, and hematological and biochemical tests.
In Section 3 we focus on investigating the nature of online food preferences on the four different dimensions described above.
The tool implements diverse numeric indicators that are associated with eight quality dimensions described in the 5S quality model.
In the following, for each cluster of dimensions described above, we provide definitions for some selected dimensions and examples of possible metrics.
From the previous experiments, we know that all patients, and in particular all patients of one outcome class, are similar to each other in the dimensions described above.
Instead, in our framework, the manifestation dimensions describe how the combination of processes is manifest in the system and the nature of those manifestations.
In this section we discuss key policy choices that would need to be considered along some of the dimensions described above in order to achieve this objective.
Clearly, many other dimensions, described in the previous sections, both specific for big data and for more traditional ones, can be applied to short texts.
The remaining two dimensions describe attitudes to time (sequential vs. synchronic) and the environment (inner-directed vs. outer-directed) (Browaeys and Price, 2008:82008
(x t,k),u t,k),y t,k)) are state, input and output variables, (A,A_{d},B,C) are the matrices with appropriate dimensions describing the system in the state space.
