Fuzzy set theory is utilized to address the uncertainty in the decision-making process.
Robust optimization approaches have been utilized to address the uncertainty in traffic signal timing optimization.
Data on seismic tomography, peninsular geomorphology and inferences on continuum of subcrustal structures are utilized to address this enigma.
The proposed framework can be utilized to address the difficult and challenging problem of transferring tasks and skills to humanoid robots.
At last, a skeleton-based path planning method is utilized to address the long and narrow geometry to improve the deposition performance and surface quality.
Also, a two-stage stochastic programming method is utilized to address different uncertainties such as wind speed and solar radiations as well as electricity and heat demands.
This report summarizes the bioavailability challenges currently faced in drug discovery, and the design and testing methods and strategies currently utilized to address the challenges.
A specific example case of single molecule transport and localized interaction energetics in a specific cell phase has been utilized to address the diffusion quite clearly.
As engineering-based approaches have been more frequently utilized to address biological questions, we discuss opportunities whereby engineering techniques may be employed to better understand the physical and biochemical factors controlling ROS expression.
In some recent works, e.g., Yin (2008) and Li (2011), robust optimization models have been utilized to address uncertainty in traffic demand and to design fixed-timed signal control for oversaturated intersections.
Consequently, two versatile, computationally efficient and self-adaptive multi-resolution utilities namely, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the ensemble empirical mode decomposition (EEMD) algorithms are utilized to address these data non-stationarity issues, which if not resolved can lead to model prediction inaccuracies.
