In spite of posing disadvantages such as complicated procedures, high expanding, and being time consuming, the models by gene manipulation were unique for investigating the AVM pathogenesis and testing new therapies.
However, performance of an OGTT is time consuming, and models based on measurement of the fasting plasma glucose (FPG) concentration and plasma lipid profile, in addition to medical history and anthropometric measurements, have been developed to predict the future risk of type 2 diabetes (3– 8).
The simulation is simple and capable of easily representing complex geometries such as randomized structures or curved contours which would be difficult and time consuming to model analytically.
Since, experiments are very time consuming, a model, which allows for solubility predictions in solvent mixtures based on less experimental data is desirable for efficiency.
Since experiments are very time consuming, a model which allows for solubility predictions in pure solvents and solvent mixtures based only on a small amount of experimental data is required.
On the other hand, the quasi-dimensional model provides information concerning the local in-cylinder temperature distribution, and describes qualitatively correctly the way the cylinder design affects the in-cylinder flow and temperature fields, as revealed by comparing its results with the corresponding ones obtained with the more accurate and time consuming CFD model.
From a practical perspective, models that are easy to generate, cheap and develop in a timely manner will be favoured over expensive and time-consuming models.
For accomplishment of such an aim, a neural network model of crankshaft and connecting rod bearings in an internal combustion engine is developed as an alternative for the complicated and time-consuming models.
These very costly and time-consuming models are common and represent only a specific point in time.
In the case of the Rt system, compared to exhaustive fits to the entire space of 58 (g, h) models, this algorithm stops before fitting the most time consuming over-parameterized models (those with three parameters or higher) though it identifies the exact same top 13 (Table 2) and top 7 (Table 4) models.
