IN an experiment with three factors at three levels each, the experimenter may be willing to sacrifice information on certain components of the two-factor ...

In production engineering, the identification of optimal process parameters is essential to advance product quality and overall equipment effectiveness. Optimizing and adapting process parameters ...

Design of Experiments (DOE) is a methodology misunderstood by many, understood by some, and actively used by even fewer than that. Wherever it does get used, though, it has the ability to completely ...

We describe biosensor elements that are capable of identifying individual DNA strands with single-base resolution. Each biosensor element consists of an individual DNA oligonucleotide covalently ...

Abstract: Microwave device design increasingly relies on surrogate modeling to accelerate optimization and reduce costly electromagnetic (EM) simulations. This article presents a spectral Bayesian ...

Wix holds the top spot in 2026, thanks to its combination of extensive business tools, powerful AI-features, super-easy-to-use interface, and responsive, professional support. Of course, the best ...

Abstract: Current distributed processing of site landscape images suffers from uneven sample distribution and multi-task gradient conflicts, which can easily lead to poor detection performance in ...

We will keep our notes and code on dealing with censored variables in Bayesian models in this repo. My initial idea for this is that we can basically treat each worked out example or section that we ...

Download the code and put it somewhere on the MATLAB path. In MATLAB, go into the eeg_example directory and open vRSA_demo_run_all.m . This will download the data and run the analyses. This toolbox ...