A multivariate predictive model for mortality was constructed by using the variables that had significant interactions with the rate of demise (P ≤.1).
We do not enter into details of the minimization problem defining (mathtt {KFR}), which could also be turned into a convex one by using the variables ((varrho, varrho mathbf {v}, varrho u)), and of its equivalent formulations.
The differential equation with respect to Δτ s,i is directly obtained from Eq. 3, and it is obvious that the evaluation of dΔτ s,i /dt on each sub-fault i can be executed by using the variables on its own sub-fault only.
The results show that Dam Failure Risk can be estimated by using the variables Dam Height, Dam Length, Maximum Flood Water Volume, Flood Water Surface Area, Mean Annual Rainfall (based on Met Office data), Altitude, Catchment Size, Urban Catchment Proportion, Forest Catchment Proportion and Managed Maximum Flood Water Volume.
The final models were obtained by using the variables that minimized Akaike's Information Criterion AICC) [20].
By using the variables shown in Table 2, the multivariate logistic regression model was constructed using the backward selection approach to form the risk score (RS) formula.
By using the variable exposure time imaging, we can suppress motion blur of bright regions.
A control scheme to reduce the torsional vibration in servomechanism systems by using the variable structure (VSC) concept is presented.
By using the variable rock resistivity parameters, precisely water saturation can be calculated for low permeability sandstones evaluation.
By using the variable exposure time imaging, the motion blur of images can be suppressed efficiently, and we can obtain clear HDR images from a single shot.
