[HTML][HTML] Uncertainty in measurement: a review of Monte Carlo simulation using Microsoft Excel for the calculation of uncertainties through functional relationships …

I Farrance, R Frenkel - The Clinical Biochemist Reviews, 2014 - ncbi.nlm.nih.gov
Abstract The Guide to the Expression of Uncertainty in Measurement (usually referred to as
the GUM) provides the basic framework for evaluating uncertainty in measurement. The …

High-performance organic photovoltaic cells under indoor lighting enabled by suppressing energetic disorders

W Wang, Y Cui, T Zhang, P Bi, J Wang, S Yang… - Joule, 2023 - cell.com
Organic photovoltaic (OPV) cells have exhibited great advantages for indoor applications.
However, large energetic disorder restricts the performance of OPV cells under low …

The top-down approach to measurement uncertainty: which formula should we use in laboratory medicine?

F Martinello, N Snoj, M Skitek, A Jerin - Biochemia Medica, 2020 - hrcak.srce.hr
Sažetak Introduction: By quantifying the measurement uncertainty (MU), both the laboratory
and the physician can have an objective estimate of the results' quality. There is significant …

Adaptive Monte Carlo and GUM methods for the evaluation of measurement uncertainty of cylindricity error

X Wen, Y Zhao, D Wang, J Pan - Precision Engineering, 2013 - Elsevier
Measurement uncertainty is one of the most important concepts in geometrical product
specification (GPS). The “Guide to the expression of uncertainty in measurement (GUM)” is …

Comparison of GUM and Monte Carlo methods for evaluating measurement uncertainty of perspiration measurement systems

A Chen, C Chen - Measurement, 2016 - Elsevier
Measurement uncertainty is an important parameter to express measurement results
including means and reliability. The uncertainty analysis of the biomedical measurement …

Addressing uncertainty on machine learning models for long-period fiber grating signal conditioning using Monte Carlo method

FO Barino, AB Dos Santos - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The massive adoption of machine learning (ML) and artificial intelligence models in the field
of instrumentation and measurement has raised several doubts concerning the validity of …

Evaluation of measurement uncertainty based on grey system theory for small samples from an unknown distribution

LF Han, WY Tang, YM Liu, J Wang, CF Fu - Science China Technological …, 2013 - Springer
To evaluate measurement uncertainty for small sample size and measurement data from an
unknown distribution, we propose a grey evaluation method of measurement uncertainty …

A Monte Carlo method for analyzing systematic and random uncertainty in quantitative nuclear magnetic resonance measurements

G Khirich - Analytical Chemistry, 2021 - ACS Publications
Quantitative nuclear magnetic resonance (qNMR) is a powerful analytical technology that is
capable of quantifying the concentration of any analyte with exquisite accuracy and …

Measurement uncertainty calculations for pH value obtained by an ion-selective electrode

J Wiora, A Wiora - Sensors, 2018 - mdpi.com
An assessment of measurement uncertainty is a task, which has to be the final step of every
chemical assay. Apart from a commonly applied typical assessment method, Monte Carlo …

Combining Nordtest method and bootstrap resampling for measurement uncertainty estimation of hematology analytes in a medical laboratory

M Cui, L Xu, H Wang, S Ju, S Xu, R Jing - Clinical Biochemistry, 2017 - Elsevier
Background Measurement uncertainty (MU) is a metrological concept, which can be used for
objectively estimating the quality of test results in medical laboratories. The Nordtest guide …