Results 51 to 60 of about 3,517,629 (284)
Robust data analysis for factorial experimental designs: Improved methods and software [PDF]
Factorial experimental designs are a large family of experimental designs. Robust statistics has been a subject of considerable research in recent decades. Therefore, robust analysis of factorial designs is applicable to many real problems.
Sarmad, Majid
core
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Background The main obstacle facing the utilization of microbial enzymes in industrial applications is the high cost of production substrates. As a result of the mentioned different wastes (coffee powder waste, dates nawah powder, molokhia stems, pea ...
Walaa A. Abdel Wahab +6 more
doaj +1 more source
Human impacts on stream ecosystems are expected to intensify with population growth and climate change. Decisive information on how stream communities respond to cumulative human impacts is therefore integral for protecting streams draining multi-use ...
Nolan J.T. Pearce +4 more
doaj +1 more source
Statistical optimization of dithranol-loaded solid lipid nanoparticles using factorial design [PDF]
This study describes a 3² full factorial experimental design to optimize the formulation of dithranol (DTH) loaded solid lipid nanoparticles (SLN) by the pre-emulsion ultrasonication method. The variables drug: lipid ratio and sonication time were studied at three levels and arranged in a 3² factorial design to study the influence on the response ...
Gambhire, Makarand Suresh +2 more
openaire +4 more sources
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
Flax Composites With Improved Interfacial Strength Through Microbially Induced Mineral Precipitation
A bio‐inspired biomineralization strategy introduces an additional hierarchy to flax fiber composites. By controlling microbe‐mediated mineral particle deposition through tuned salt concentrations, stress transfer within the natural fiber composite is enhanced.
Deniz Sayinbas +5 more
wiley +1 more source
Statistics applied to plant micropropagation: a critical review of inadequate use
Statistical analyses are an essential part of scientific research. Various procedures since the preparation of the experiment have an impact on the statistical procedures adopted. Therefore, a correct planning implies a precise analysis.
Vanderley José Pereira +4 more
doaj +3 more sources
Holistic Design of Experiments Using an Integrated Process Model
Statistical experimental designs such as factorial, optimal, or definitive screening designs represent the state of the art in biopharmaceutical process characterization.
Thomas Oberleitner +3 more
doaj +1 more source
Statistical Analysis of Efficient Unbalanced Factorial Designs for Two-Color Microarray Experiments [PDF]
Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly ...
openaire +2 more sources

