However, until the 1970s, most models relied on adaptive expectations, which assumed that expectations were based on an average of past trends.
Most business models rely on information technology for its core functionalities and processes [39, 40] and, thus, mission-critical data integrity and availability must be ensured.
Moreover, our model implies that the underlying data, shared among processing steps, should be done via tabular data stores; whereas most workflow models rely on files to store and share the data, which cannot achieve the same scalability and flexibility.
Most prognostic models rely on variables recorded within 24 hours of admission to predict the mortality rate of patients in the intensive care unit (ICU).
Most existing models rely on a gradual change in numbers of observed events and are not adapted for data exhibiting a sudden spike in case numbers at an unexpected point in time.
Most of these models rely on the diffusion equations based on the composition of liposomes and conditions of release.
The occurrence of the counter-gradient diffusion phenomenon will of course lead to the collapse of the "gradient-diffusion hypothesis," on which most conventional turbulence models rely.
However, most of these models rely on the simultaneous occurrence of two Fisherian runaway processes, which will only occur in the presence of large variation in female preferences.
Most of these models rely on the reverse passive Arthus reaction, a localized alveolitis triggered by deposition of heterologous immune complexes.
Most of these models rely primarily on presence/absence or presence only data for species distributions, and temperature and precipitation interpolations from existing weather station data adjusted using digital elevation models for environmental conditions, but levels of sophistication are increasing rapidly as the field matures (Guisan et al. 2006).
