Results 21 to 30 of about 11,712,389 (339)

Olympus: a benchmarking framework for noisy optimization and experiment planning [PDF]

Machine Learning: Science and Technology, 2020
Research challenges encountered across science, engineering, and economics can frequently be formulated as optimization tasks. In chemistry and materials science, recent growth in laboratory digitization and automation has sparked interest in ...
Florian Hase, Matteo Aldeghi, Riley J. Hickman, L. Roch, M. Christensen, E. Liles, J. Hein, Alán Aspuru-Guzik   +7 more
semanticscholar   +1 more source

How to Accelerate R&D and Optimize Experiment Planning with Machine Learning and Data Science.

Chimia (Basel), 2023
Accelerating R&D is essential to address some of the challenges humanity is currently facing, such as achieving the global sustainability goals. Today's Edisonian approach of trial-and-error still prevalent in R&D labs takes up to two decades of ...
Daniel Pacheco Gutiérrez, Linnea M. Folkmann, Hermann Tribukait, L. Roch   +3 more
semanticscholar   +1 more source

Plot size and number of replications for ryegrass experiments [PDF]

Ciência Rural, 2020
: The objective of this research was to determine the optimal plot size and the number of replications to evaluate the fresh matter of ryegrass sown to haul.
Marcos Toebe, Alberto Cargnelutti Filho, Juliana Oliveira de Carvalho, Francieli de Lima Tartaglia, Alessandra Ferreira Cortes, Anderson Chuquel Mello, Patrícia Jesus de Melo   +6 more
doaj   +1 more source

Plot size and number of replicates for experiments with forage sorghum [PDF]

Pesquisa Agropecuária Brasileira, 2022
The objective of this work was to define the optimal plot size and number of replicates for the evaluation of the fresh weight of sorghum (Sorghum bicolor) hybrids.
Marcos Toebe, Alberto Cargnelutti Filho, Rafael Rodrigues de Souza, Franciele dos Santos Soares, Anderson Chuquel Mello, Patrícia Jesus de Melo, Lucas Santos da Silva   +6 more
doaj   +1 more source

Update 2.0 to "Takin: An open-source software for experiment planning, visualisation, and data analysis", (PII: S2352711016300152)

SoftwareX, 2021
We report a major new release of the inelastic neutron scattering software Takin. The software package comprises programme modules for experiment planning, scan visualisation and data treatment at neutron triple-axis spectrometers.
T. Weber
semanticscholar   +1 more source

Experiments with proof plans for induction [PDF]

Journal of Automated Reasoning, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alan Bundy, Frank van Harmelen, Jane Hesketh, Alan Smaill   +3 more
openaire   +3 more sources

К вопросу устойчивости динамической системы функционирования сообществ социальной сети

Vestnik KRAUNC: Fiziko-Matematičeskie Nauki, 2022
В статье рассматривается динамическая система функционирования сообществ социальной сети и приводится набор численных экспериментов позволяющих проверить устойчивость системы дифференциальных уравнений.
Охапкина, Е.П., Мещеряков, Р.В., Исхакова, А.О., Исхаков, А.Ю.   +3 more
doaj   +1 more source

Methodology for finding parameters of cutting transitions in APQP process of preproduction of new automotive components

Омский научный вестник, 2023
The article discusses the content of the methodology for assessing the technological state of the machine tool system based on the method of planning experiments for cutting pre-designed and manufactured for special precision characteristics of ...
L. R. Safarova, S. V. Kasyanov, D. T. Safarov   +2 more
doaj   +1 more source

Takin: An open-source software for experiment planning, visualisation, and data analysis [PDF]

SoftwareX, 2016
Due to the instrument's non-trivial resolution function, measurements on triple-axis spectrometers require extra care from the experimenter in order to obtain optimal results and to avoid unwanted spurious artefacts.
T. Weber, R. Georgii, P. Böni
semanticscholar   +1 more source

Translating Natural Language to Planning Goals with Large-Language Models [PDF]

arXiv.org, 2023
Recent large language models (LLMs) have demonstrated remarkable performance on a variety of natural language processing (NLP) tasks, leading to intense excitement about their applicability across various domains.
Yaqi Xie, Chenyao Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, Harold Soh   +5 more
semanticscholar   +1 more source