Sentence examples for maximization from from inspiring English sources
In this paper, we consider value maximization from three increasingly comprehensive perspectives: artifact-, process-, and organization-focused. Based on this framework, we then identify five characteristics of common design processes, and explain and justify these characteristics in terms of value maximization.
Profit maximization from increasing land value leads to environmentally critical area loss.
Recovery maximization from horizontal well completion is a challenge in the oil industry, which is dependent on variants viz: critical rate, length of horizontal section, offset from water oil contact (WOC), withdrawal rate.
The representative household lives infinitely and pursues discounted lifetime utility maximization from consumption C, and from health, H. {displaystyle underset{t=infty }{overset{t=0}{int }}left[ ln C t)+eta ln H t)right]} exp left -frac{1}{x}tright dtkern1em upeta >0 (1). in which η presents the positive impact of healeft -frac{1}{x}tright dtkern1em
It appears that the HGT events of the highly conserved PAH-degrading gene clusters could provide practical benefits: (i) overcoming evolutionary selective pressure, (ii) acceleration of the buildup speed, and (iii) metabolic maximization from the limited genetic modules [ 9, 64].
Gilbert, J, and Tower, E. "Utility Maximization Program from Chapter 3 of Gilbert and Tower (2013)." (November 9 , 2012.
In particular, we study preprocessing methods to avoid redoing influence maximization for each mixture from scratch.
Normalized RNA expression (RNA-Seq by expectation maximization (RSEM)) data from CRC patient samples were obtained from the publically available TCGA datasets31 at https://cancergenome.nih.gov/.nih.gov/
We should note that our problem formulation shown in Figure 2(B) is the covariance maximization between u (from Y) and the weighted sum of (from ), so it can well capture the holistic correlations between response block and all input blocks.
Detection of bimodality in the distribution, the signature of a past isolation event, was performed by fitting a Gaussian Mixture Model using the Expectation-Maximization algorithm from Meng and Rubin (1993) as implemented in the R package mixtools (Benaglia et al. 2009).
We estimate model parameters by likelihood maximization using data from the Mayo Lung Project (MLP), which was a clinical trial that evaluated screening for lung cancer in the 1970s.
