Calculation of Expanded Uncertainty in Measurements Using the Kurtosis Method when Implementing a Bayesian Approach

Захаров, Ігор; Botsyura, O. A.

doi:10.1007/s11018-019-01625-x

Cited by 16 publications

(7 citation statements)

References 2 publications

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“…The uncertainty analysis was conducted to assess the consistency of the dependent parameters, and the measurement points were based on the standard deviation of each sensor. Moreover, the calculated parameters associated with the mass flowrates of each operating parameter were determined through Eq (9) [ 35 ], and the measuring point was determined through Eq (10) [ 36 ] values obtained are presented in Table 5 .

where U x … U y are different independent parameters while U is the dependent parameter, and the accuracy of each sensor device is.…”

Section: Methodsmentioning

confidence: 99%

The experimental study of dehumidification and regeneration processes in a fin and tube liquid desiccant system

Indrawan

Lubis

Nasruddin

et al. 2022

Case Studies in Thermal Engineering

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where U x … U y are different independent parameters while U is the dependent parameter, and the accuracy of each sensor device is.…”

Section: Methodsmentioning

confidence: 99%

The experimental study of dehumidification and regeneration processes in a fin and tube liquid desiccant system

Indrawan

Lubis

Nasruddin

et al. 2022

Case Studies in Thermal Engineering

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“…Te length of the interval centred on the mean value decreases as the sample size increases. We use the following formula to calculate the uncertainty U [27]:…”

Section: (2)mentioning

confidence: 99%

Analytical Validation of Smartphone Spectroscopic Technic Used in an Educational Kinetic Study

Raissi

Fakhfakh

2023

International Journal of Analytical Chemistry

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Use of smartphone-based spectroscopy is showing a constant growth since last year. It presents the advantage of being widely available for everyone. The most important thing is that it is still a low-cost method adapted to the education context. However, as all analytical methods, it should be validated to ensure the reliability of its results. In this study, we present the steps of the validation process with its statistical tests applied to the dosage of di-iode. Shapiro–Wilk test revealed that our method has a random character. Homogeneity of variance analyses using the Cochran test confirmed the precision of the method. The Fisher test revealed the linearity of the model of correlation between I2 concentration and the response. The relation between response and concentration is A = 1000 C + 0.002. From the parameters of the linear regression of the model, we deduced the limits of quantification and XLq = 4·10−5 mol·L−1 and XLd = 1·10−5 mol·L−1. Thanks to tightness of the sample, the method of I2 dosage was successfully applied in iodine quantification to monitor acetone iodination during time in the context of kinetic studies with minimum system trouble. Being low cost, this method can facilitate access to physical methods in educational laboratories.

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“…A reliable evaluation of the expanded uncertainty cannot be obtained without accounting for the laws of distribution for input quantities, which is usually done by the Monte Carlo method (MCM) [4]. For calibration issues, a reliable evaluation of the expanded uncertainty can be obtained using the kurtosis method [12]. Its use makes it possible to automate the calculation of uncertainty, and the expanded uncertainty itself will be close to that obtained by MCM.…”

Section: Experimental Data Processingmentioning

confidence: 99%

Main stages of calibration of measuring instruments

Zakharov,

Botsiura,

Zakharov

et al. 2023

УМЖ

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The main stages of calibration of measuring instruments are described. The stage of preparation for calibration and its main steps are considered: setting a measurement task, choosing a method and equipment, choosing (developing) calibration methods and their verification (validation). The content of the measurement experiment is presented together with the main measurement methods that can be used to calibrate the indications of measuring instruments and material measures. The main steps of experimental data processing, which lead to the estimation of the numerical value and uncertainty evaluation of the measurand being calibrated, are considered. The preparation of calibration results, including the uncertainty budget and calibration certificate, is described. Procedures for assessing the probability of compliance of a calibrated measuring instrument and material measure with the specified metrological characteristics, as well as for validating their calibration methods, are considered.

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Calculation of Expanded Uncertainty in Measurements Using the Kurtosis Method when Implementing a Bayesian Approach

Cited by 16 publications

References 2 publications

The experimental study of dehumidification and regeneration processes in a fin and tube liquid desiccant system

The experimental study of dehumidification and regeneration processes in a fin and tube liquid desiccant system

Analytical Validation of Smartphone Spectroscopic Technic Used in an Educational Kinetic Study

Main stages of calibration of measuring instruments

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