On the whole, most studies use students as participants.
Currently, most studies use the co-density formulation (Braginsky and Roberts 1995).
Most studies use a single general purpose neural networks for fault diagnostics with limited reliability and accuracy.
The theorems and the experiments focus on within-respondent variability, but most studies use between-respondent designs.
Most studies use a binary conceptual model of landscapes (habitat versus non-habitat) and static measures of biodiversity.
Most studies use optical motion capture systems, which usually induce space limitations and where walk is thus recorded on a treadmill.
Most studies use first-order kinetics for both the furfural degradation [5, 15, 22, 26, 33, 37] and pentose dehydration reactions [6, 9, 28, 38].
The review was based on the guidelines proposed by Kitchenham (2007) [13] and shows that most studies use an informal process to develop usability heuristics.
Furthermore, while travel is an inherently linear activity, most studies use coarse, zonal averages, likely missing key details important to pedestrians and bicyclists.
In addressing this issue, most studies use complete case analysis, which excludes cases with missing data, thus potentially introducing selection bias.
At present, most studies use magnetic resonance imaging, which allows for excellent grey- and white-matter resolution in cortical and subcortical areas and detection of brain tissue pathology.
