01. Design and Analysis of Experiments

TL;DR: This study employs response surface methodology and multi-objective optimization to predict and optimize the performance of an opposed-piston free-piston engine generator, identifying key parameters and their effects on thermodynamic performance, achieving 64.74% efficiency and 5.10 kW power output.

TL;DR: In this article , an experimental evaluation of a Venturi and Venturi-Vortex microbubble aeration system is presented, taking as input variables the water-air flow ratio, water renewal time and area-volume ratio of the water tank.

TL;DR: In this paper, a distribution-independent approach of modeling isometric log-ratio-transformed shares of an arbitrary number of discrete particle size classes is presented, which allows using standard empirical modeling techniques, and the mathematically proper calculation of confidence and prediction regions.

TL;DR: In this article , the authors investigated the utilization of alkali-activated granular blast furnace slag and fly ash (FA) for stabilizing rammed earth materials and assessing their mechanical and durability properties.

TL;DR: In this paper, it is shown that Tukey's test of additivity is equivalent to the test of a regression coefficient in a model with a single covariate, and the derivation given is general for the standard experimental designs, such as complete and incomplete randomized blocks and Latin squares.

TL;DR: In this paper, the authors provide a detailed discussion of the calculation of sample sizes using the width of confidence intervals for pairwise comparisons, treatment-versus-control comparisons, trends, and difference of averages.

TL;DR: In this article, an alternate formula for computing the adjusted treatment sum of squares for Group Divisible Partially Balanced Incomplete Block Designs (GD-PBIB) was proposed.

TL;DR: The authors summarize information scattered in the technical literature on a subject too new to be included in most textbooks, but which is of interest to statisticians, and those who use statistics in science and education, at an advanced undergraduate or higher level.