Chufa heat tolerance was evaluated based on parameters of CO2 gas exchange, the state of its photosynthetic apparatus (PSA), and intensity of peroxidation of leaf lipids.
We also propose some new algorithms based on parameter optimization and evaluate their performance together with the existing ones.
The methods are evaluated based on parameter estimation procedures applied (including introduction of the sequential Monte Carlo sampler in RBLM), the capability of the resulting sequences to reproduce standard validation statistics, and the representation of observed rainfall variability and intermittency, within-day wet spells, and extreme rainfall percentiles.
The statistical model is based on individual pore contribution parameters evaluated by finite element simulations for a small pore subset selected using the design of experiments approach, so there is no need to solve the elasticity problem for all pores in the material.
We employed a Bonferroni correction based on: the number of parameters evaluated (3), the number of ROI pairs per each matrix (6,670), the number of fixed density of thresholds (6), the number of bootstrapped data (5,000), and the number of tests we conducted (one-way ANOVA, 6) to evaluate the differences between the 5 groups for each parameter.
Conformity of the classification under specific phenotypes within field studies and classification of trees based on quantitative parameters were evaluated using discriminant analysis.
Their parameters are derived based on evaluated data.
The model parameters, evaluated based on the measurements of thicknesses as function of Cu2 + concentration and exposure time, were further validated by comparing the prediction of the model with another set of independent measurement; here, the depletion of Cu2 + ions in the conditioning solution above the reacting gel is measured as function of time.
Hence, the performance of the proposed FTCSPM is evaluated based on performance evaluation parameters viz., packet delivery ratio, energy consumption, average end-to-end delay, packet drop rate and throughput.
It is known that traditional methods to measure oral health are based on clinical parameters, which only evaluate the physical conditions based on judgments established by professionals - normative assessment - minimizing the psychosocial consequences of the oral conditions [ 10].
