Covers the propagation of uncertainty through the generation of probability density functions.
Delves into applying thermodynamics in metabolic pathways, discussing constraints, bi-directional reactions, and estimation methods.
Covers the propagation of uncertainty in model measurements and the importance of understanding errors.
Discusses error minimization in Bayesian inference and the importance of prior knowledge in the inference process.
Explores the propagation of uncertainty in correlated variables and extreme correlations, Tchebychev inequality, confidence intervals, and Taylor series development.
Explores uncertainty analysis in Life Cycle Assessment, covering sensitivity, probability functions, parameter estimation, pedigree approach, and uncertainty propagation.
Explores uncertainty sources in Life Cycle Assessment, emphasizing the need for accurate data and precise measurements.
Delves into real-world games, negotiation strategies, and optimal agreements beyond Nash equilibrium.
Discusses measurement principles through examples of calibration, sensitivity, and optical measurement techniques.
Explores optimization, simulation, data analysis, and the importance of considering more than just the mean in engineering systems.
