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 ...

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

Neuroscience is a multidisciplinary science that is concerned with the study of the structure and function of the nervous system. It encompasses the evolution, development, cellular and molecular ...

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 ...

Information Source Finding in Networks: Querying with Budgets 2020-10-22 Part ... Part of this work was presented at the IEEE INFOCOM 2017 (arXiv:1805.03532) and IEEE ISIT 2018 (arXiv:1711.05496) ...