Specifically two approaches are compared – approximate method based on evaluation of simplified kinetics and a more comprehensive, simulation-based method that utilizes the evaluation of more detailed kinetic models.
In this study, a simulation-based method that utilizes a virtual machine tool (VMT) to optimize the machining condition is proposed.
To obtain an optimized walking path with minimum dose without considering the pre-designed road networks, a sampling-based method that utilizes the rapidly exploring random tree star (RRT*) algorithm, applicable in both continuous and discrete radiation fields, was proposed and implemented.
Therefore, we designed a permutation-based method that utilizes the empirical null distribution to evaluate the (empirical) FDR when multi-dimensional datasets are involved.
Unlike previous module inference tools which are static statistics-based methods, HIMIA is a dynamic system model-based method that utilizes the dynamic nature of time series gene expression data.
These two approaches utilize reaction flux obtained by a Linear Programming (LP) based method that can contribute to the discovery of potential novel biomarkers.
However, the processes still had some shortcomings and therefore the research team developed a form based method that property owners and builders can utilize for a successful removal of the indoor air problems.
In this paper, we propose a Particle Swarm Optimization based motif-finding method that utilizes a proven Bayesian Scoring Scheme as the fitness function.
These criteria were selected based on a method that utilizes a reverse database false positive model [37].
The criteria selected for filtering are based on a method that utilizes a reverse database false positive model which has a ∼95% confidence over an entire protein dataset [41].
The classification is based on machine learning method that utilizes a deep convolutional neural network.
