Measurement Uncertainty

This paper concerns the problem of actively searching for and localizing ground features by a coordinated team of air and ground robotic sensor platforms. The approach taken builds on well known Decentralized Data Fusion (DDF) methodology. In particular, it brings together established representations developed for identification and linearized estimation problems to jointly address feature detection and localization. This provides transparent and scalable integration of sensor information from air and ground platforms. As in previous studies, an Informationtheoretic utility measure and local control strategy drive the robots to uncertainty reducing team configurations. Complementary characteristics in terms of coverage and accuracy are revealed through analysis of the observation uncertainty for air and ground on-board cameras. Implementation results for a detection and localization example indicate the ability of this approach to scalably and efficiently realize such collaborative potential.

High-performance liquid chromatography (HPLC) to determine shikimic acid is used as a complementary tool to differentiate wine varieties. In order to correctly classify, measurement uncertainty of shikimic acid by HPLC in red wine was estimated considering the following components: uncertainty associated with the preparation of shikimic acid stock solution, uncertainty associated with quantification using a calibration curve, and uncertainty associated with precision. The most important contribution to total uncertainty was the method precision. The expanded uncertainty (U) for different wine varieties was between 2.6 and 8.5%. The method was applied to determine the concentration of shikimic acid in different emerging wine varieties cultivated in Chile, such as Carmenère, Shiraz, and Pinot Noir, comparing them with classical varieties, such as Cabernet Sauvignon and Merlot. Shiraz wines presented lower shikimic acid concentrations (between 27 and 86 mg L−1 with U (k=2) = 2.6%) than Cabernet Sauvignon wines (between 41 and 142 mg L−1 with U (k=2) = 8.1%), but their concentrations were higher than found in Merlot (from 9 to 41 mg L−1 with U (k=2) = 4.3%) and Carmenère wines (between 7 and 49 mg L−1 with U (k=2) = 5.8%). Pinot Noir was the variety with the lowest concentration of this acid (7–14 mg L−1 with U (k=2) = 8.5%).

There are situations in experimental work where largejluctuations of the measurand are experienced, either because of inherent variations of the observed quantity or because of the complexity of the system process leading to the output quantity. A large spread of the measuredvalues around the center value results. It often appears to the experimenter that the spread of values around the mean is not symmetric, rather, values above the mean obtained by multiplying by a certain factor are approximately as likely as those obtained by dividing the mean value by the samefactor. A log-normal distribution thus appears to be a candidate for a representation of the distribution of the observed quantify, at least as a simplrfiing assumption, when such distribution cannot be assumed a priori on the basis of physical reasoning. A system where large variations of the observed quantity result can be e.remplified by the radiotor-to-receiver transmission in the dominant presence of reflecting surjaces, such as in a screened room. Overall, large variations are often observed in EMC work, where we are usually faced with complex experimental orpredicfive processes. In the following we describe the procedure through which the parameters of the log-normal distribution fitting a given set of experimental outcomes are obtained. This description is applied to the measured field distribution in a screened room.

Target tracking in clutter is usually evaluated using simulations. The statistics of the overall tracking performance are gathered, including the false track discrimination, the root mean square trajectory tracking errors, or some combined measure of performance, e.g. OSPA. These performance measures treat the target tracking filter as a black box; i.e. the performance of separate target tracking algorithm components is neither considered nor evaluated. In this paper we partition the target tracking algorithm into the estimation and the data association components and consider the performance measures for the data association component. Three performance measures are proposed and evaluated: the fidelity measure, the selection measure and the competence measure which combines capabilities of the fidelity and the selection measures.

In the context of quality assurance strategies, statistical process control techniques and conformance testing are necessary to perform a correct quality auditing of process outcomes. However, data collection is based on measurements and every measurement is intrinsically affected by uncertainty. Even if adopted instruments are in a condition of metrological confirmation, random and systematic measurement errors can not be completely eliminated. Moreover, the consequence of wrong measurement-based decisions can seriously decrease company profits because of larger repairing and shipping costs, as well as for the loss of reputation due to customers' dissatisfaction. This paper deals with a theoretical analysis aimed at estimating the growth in decisional risks due to both random and systematic errors. Also, it provides some useful guidelines about how to choose the Test Uncertainty Ratio (TUR) of industry-rated measurement instruments in order to bound the risk of making wrong decisions below a preset maximum value.

A method was validated for the multi-residue analysis of 82 pesticides in grapes at ≤25 ng/g level. Berry samples (10 g) mixed with sodium sulphate (10 g) were extracted with ethyl acetate (10 mL); cleaned by dispersive solid phase extraction and the results were obtained by liquid chromatography–tandem mass spectrometry. Reduction in sample size and proportion of ethyl acetate for extraction did not affect accuracy or precision of analysis when compared to the reported methods and was also statistically similar to the QuEChERS technique. The method was rugged (HorRat < 0.5) with <20% measurement uncertainties. Limit of quantification was <10 ng/g with recoveries 70–120% for most pesticides. The method offers cheaper and safer alternative to typical multi-residue analysis methods for grape.

Uncertainty is ubiquitous in science, engineering and medicine. Drawing conclusions from uncertain data is the normal case, not an exception. While the field of statistical graphics is well established, only a few 2D and 3D visualization and feature extraction methods have been devised that consider uncertainty. We present mathematical formulations for uncertain equivalents of isocontours based on standard probability theory and statistics and employ them in interactive visualization methods. As input data, we consider discretized uncertain scalar fields and model these as random fields. To create a continuous representation suitable for visualization we introduce interpolated probability density functions. Furthermore, we introduce numerical condition as a general means in feature-based visualization. The condition number-which potentially diverges in the isocontour problem-describes how errors in the input data are amplified in feature computation. We show how the average numerical condition of isocontours aids the selection of thresholds that correspond to robust isocontours. Additionally, we introduce the isocontour density and the level crossing probability field; these two measures for the spatial distribution of uncertain isocontours are directly based on the probabilistic model of the input data. Finally, we adapt interactive visualization methods to evaluate and display these measures and apply them to 2D and 3D data sets.

This paper considers measures of uncertainty used in economic estimation. Our …rst contribution is to address the theoretical relationship between cross-section and time series measures, highlighting the reasons why these might diverge. In a subsequent empirical section, we compare measures of uncertainty, all of which are based on underlying data on optimism from an established UK survey database, managed by the main employers' organization, the CBI. We measure uncertainty at industry level in three ways: by cross-section dispersion of optimism expectations, by a GARCH series based on the optimism data and by an unconditional volatility measure based on the same data.

The objective of this research was to test suitability of the Dumas combustion method to completely substitute the Kjeldahl method in routine laboratory determination of crude protein content in cereals and oilseeds. The validation of the method demonstrated that it is able to determine crude protein content in cereals and oilseeds in an efficient and accurate manner, with a detection

This paper presents a new method for critical WU [8-9]). In 1987, Slutsker & Scudder [lo] developed a measurement identification. A measurement is said to be method of network observability based on the reduction of critical, in observability sense, if its removal from the the measurement Jacobian matrix, and finally, in 1995 measurement set leads the system to lose observability. The Bretas [14] developed a methodology to analyze the proposed method is based on the analysis of the measurement observability through the triangular factorization of the gain matrix and path graph concepts. Using the concepts of jacobian matrix structure as presented by Slutsker & Scudder [lo] (for network observability purpose). It does allow to identify the critical measurements without any calculation or observability contained in the aforementioned researches, even solving algebraic equations. It does not have combinatory Some methods to identify measurements like nature, being simple and fast. In order to clarify the elements et all and Crainic et all were formulated. The methodology and show its simplicity, two numerical examples method Of Clements et all [4] does not require any are provided. One to illustrates how the observability analysis calculation but it presents combinatorial nature. The method works and the other to show how the proposed methodology of Crainic et all [l 13 is based on the measurement to branch identifies critical measurements. The proposed methodology is

We address the issue of the relation between local quantities and the uncertainty principle. We approach the problem by defining local quantities as conditional standard deviations, and we relate these to the uncertainty product appearing in the standard uncertainty principle. We show that the uncertainty product for the average local standard deviations is always less than or equal to the standard uncertainty product and that it can be arbitrarily small. We apply these results to the short-time Fourier transform/spectrogram to explore the commonly held notion that the uncertainty principle somehow limits local quantities. We show that, indeed, for the spectrogram, there is a lower bound on the local uncertainty product of the spectrogram due to the windowing operation of this method. This limitation is an inherent property of the spectrogram and is not a property of the signal or a fundamental limit. We also examine the local uncertainty product for a large class of time-frequency distributions that satisfy the usual uncertainty principle, including the Wigner distribution, the Choi-Williams distribution, and many other commonly used distributions. We obtain an expression for the local uncertainty product in terms of the signal and show that for these distributions, the local uncertainty product is less than that of the spectrogram and can be arbitrarily small. Extension of our approach to an entropy formulation of the uncertainty principle is also considered.

This paper presents a multisensor, multitarget tracking simulator TRACKER that can be used to demonstrate and evaluate airborne early warning and control surveillance systems. TRACKER is a Level 1 fusion surveillance software package that generates a unified object state vector and its measure of uncertainty for each tracked object based on cluttered multitarget augmented (kinematic and discrete type) measurements from

The main objective of this work is to present a method for measuring the specific heat of single metallic, carbon, and ceramic fibers at very high temperature. The difficulty of the measurement is due to the microscale of the fiber ͑Ϸ10 m͒ and the important range of temperature ͑700-2700 K͒. An experimental device, a modelization of the thermal behavior, and an analytic model have been developed. A discussion on the measurement accuracy yields a global uncertainty lower than 10%. The characterization of a tungsten filament with thermal properties identical to those of the bulk allows the validation of the device and the thermal estimation method. Finally, measurements on carbon and ceramic fibers have been done at very high temperature.

This paper describes the methodology developed for characterizing a commercial charge-coupled device (CCD) camera as a luminance meter for analyzing lighting systems and especially for measurements in road light plants. Today, several luminance meters based on commercial CCD cameras are on the market. They are very attractive for the lighting engineer: The availability of a high number of closely spaced small detectors (pixels) on a single chip permits analyses almost impossible with a traditional luminance meter. These commercial-industrial CCD cameras are sold at prices lower than scientific grade ones. They are factory equipped with a dedicated filter to reach the correct photopic sensitivity V( ), and they are factory calibrated in luminance SI units. The main counterparts in using these cameras are in the difficulties to define the measurement accuracy and the influence of the environment luminance on the measured values of the framed scene, in the low resolution of their A/D converter (usually 8 or 12 bit), and the higher noise level (usually the CCD chip is not cooled). To reach the measurement accuracy required by lighting norms, it is necessary to characterize metrologically a camera and quantify all the possible external influences which could degrade its performances, in real measurement situations, and which could affect the measurement results. A carefully controlled measurement set up and operating procedure could limit the causes of errors and improve the accuracy of measurements obtained in operating conditions. In this way, the measurement uncertainties might be evaluated completely, and considerations on the results could suggest particular operating practices to limit the causes of error due to measurement setup and environmental conditions.

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Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements.In this study, PM2.5 source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM2.5 measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF.Sensitivity of the PMF2 and ME2 models to the selection of speciated PM2.5 components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle-oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM2.5 emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers.

Dyed poly(vinyl butyral) (PVB) films prepared by a simple technique of casting alcoholic solution of PVB incorporating thymol blue (TB) indicator and chloral hydrate [CCl 3 CH(OH) 2 , 2,2,2-trichloroethane-1,1-diol] on a horizontal glass plate are useful for ultraviolet radiation monitoring. These plastic films undergo colour change from yellow to red upon exposure to UV irradiation. The radiation-induced change in colour was analysed spectrophotometrically at the maximum of the visible absorption band peaking at 551 nm. These films have a pronounced response to the main UV radiation spectral regions [UVA (400-320 nm), UVB (320-280 nm) and UVC (280-180 nm)] showing a maximum sensitivity at 200 nm. The measurement uncertainty of estimating ultraviolet radiation energy incident per unit area on the films is found to be 6.6% at a confidence limit of 95% (2σ ). The study of the effect of radiance exposure, irradiation wavelength, chloral hydrate concentration and the post-irradiation stability in different storage conditions has been carried out to characterise the use of these films for actinometric monitoring ultraviolet radiation.

This paper deals with the uncertainty evaluation in indirect measurements. The attention is mainly paid to measurement models whose input quantities are modeled as correlated random variates. Moving from a past proposal related to the use of the unscented transform to overcome key limitations of current guide to the expression of uncertainty in measurement recommendations in the presence of the

in Vigna di Valle, Rome (Italy). The campaign is held at the Centre of Meteorological Experimentations (ReSMA) of the Italian Meteorological Service. A group of 30 previously selected rain gauges based on different measuring principles are involved in the Intercomparison. Installation of the instruments in the field was preceded by the laboratory calibration of all submitted catching-type rain gauges at the University of Genoa. Additional meteorological sensors (ancillary information) and the observations and measurements performed by the Global Climate Observing System/Global Atmosphere Watch (GCOS/GAW) meteorological station of Vigna di Valle were analyzed as metadata. All catching-type gauges were tested after installation using a portable calibration device specifically developed at the University of Genoa, simulating an ordinary calibration inspection in the field. This paper is dedicated to the summary of preliminary results of the Intercomparison measurements. It offers a view on the main achievements expected from the Intercomparison in evaluating the performance of the instruments in field conditions. Comparison of several rain gauges demonstrated the possibility to evaluate the performance of RI gauges at one-minute resolution in time, as recommended by the WMO Commission for Instruments and Methods of Observations (WMO-CIMO). Results indicate that synchronised tipping-bucket rain gauges (TBR), using internal correction algorithms, and weighing gauges (WG) with improved dynamic stability and short step response are the most accurate gauges for one-minute RI measurements, since providing the lowest measurement uncertainty with respect to the assumed working reference.

Micropipettes or piston pipettes are used to make the most of volume measurements in fields like health, chemistry, biology, pharmacy and genetics. Laboratories must ensure that obtained results using these instruments are reliable, for that is necessary to calibrate micropipettes using the correct method and estimate uncertainties. The objective of this work is to present the best method to calibrate micropipettes according to the describe measurement conditions. A model for the calculation of the measurement uncertainty is also described.

This paper describes instrumental measurement uncertainties and their influence on the result obtained from determination of rock sample uniaxial compressive strength and deformability. The interdependence of uncertainty contribution is analyzed and guides for improving measurement uncertainty are given. The achieved uncertainties are compared to typical uncertainties in the determination of concrete and metallic material compressive strength and deformability.

Background: The Dutch project&quot; Calibration 2000&quot; aims at harmonization of laboratory results via calibration by development of commutable, matrix-based, secondary reference materials. An alternative approach to the NCCLS EP14 protocol for studying commutability ...

Delamination is a typical defect of ceramic tiles. It originates from the presence of trapped air during pressing, and elastic recovery of the pressed material, which prevents the consolidation of the pressed material. Although delamination greatly reduces the quality of the final product, standard tests for ceramic tiles are not currently available.

This paper deals with the control and observation of an induction motor using sliding-mode technique. Our aim is to regulate the speed and the square of the rotor flux magnitude to specified references. Assuming that all the states are measured, sliding surfaces are proposed within a sliding-mode control framework. Then, the stator voltages are derived such that the sliding surfaces are asymptotically attractive. Since, in practice, the rotor fluxes are not usually measurable, a sliding-mode observer is derived to estimate the rotor fluxes. Furthermore, it is shown that our observer is robust against modeling uncertainties and measurement noise. To illustrate our purpose, we present experimental results for a 0.37-kW induction motor obtained on a digital-signal-processor-based system (TMS 320C31/40 MHz). The experimental results show that the proposed control system is robust against rotor resistance variations.

Abstract: The paper reviews the background and methodology of the primary calibration of Acoustic Emission (AE) sensors. Two practically realised basic calibration methods are described and explained. The method of reciprocity calibration is based on the reciprocity theorem. The ...

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort, the US Environmental Protection Agency (EPA) is investigating methods that relate sample characteristics to analytical performance. Predicted uncertainty levels allow appropriate study design decisions to be made, facilitating more timely and less expensive evaluations. Gy sampling theory can predict a significant fraction of sampling error when certain conditions are met. We report on several controlled studies of subsampling procedures to evaluate the utility of Gy sampling theory applied to laboratory subsampling practices. Several sample types were studied and both analyte and non-analyte containing particles were shown to play important roles affecting the measured uncertainty.

A number of approaches for evaluating recovery and its contribution to uncertainty budgets for analytical methods are considered in detail. The recovery, R, for a particular sample is considered as comprising three elements, R m , R s and R rep . These relate to the recovery for the method; the effect of sample matrix and/or analyte concentration on recovery; and how well the behaviour of spiked samples represents that of test samples. The uncertainty associated with R, u(R), will have contributions from u(R m ), u(R s ) and u(R rep ). The evaluation of these components depends on the method scope and the availability, or otherwise, of representative certified reference materials. Procedures for evaluating these parameters are considered and illustrated with worked examples. Techniques discussed include the use of certified reference materials and spiking studies, and the use of extraction profiling to predict recoveries. All the approaches discussed evaluate the recovery and its uncertainty for the analytical method as a whole. It is concluded that this is a useful approach as it reduces the amount of experimental work required. In addition, most of the required data are frequently available from method validation studies.

Given the common assumption that measurement plays an important role in the foundation of science, the paper analyzes the possibility that Measurement Science, and therefore measurement itself, can be properly founded. The realist and the representational positions are analyzed at this regards: the conclusion, that such positions unavoidably lead to paradoxical situations, opens the discussion for a new epistemology of measurement, whose characteristics and interpretation are sketched here but are still largely matter of investigation.

Stereo vision has emerged as an effective approach for contactless 3-D measurements. This paper presents a methodology for the propagation of the measurement uncertainty through stereo-vision calibration and measurement algorithms, according to international standards. The proposed procedure is compared to the reference statistical procedure for uncertainty evaluation, and the results are presented and discussed. The results proved that the proposed procedure was able to estimate the standard uncertainty even at considerable working distances from the calibrated volume with negligible processing times and far more accurately than the theoretical simplified models commonly adopted.

A high performance liquid chromatographic method with fluorimetric detection for the determination of aflatoxin M 1 (AFM 1 ) in milk has been optimized and validated according to Commission Decision 2002/657/EC by using the conventional validation approach. The procedure for determining selectivity, recovery, precision, decision limit (CC α ), detection capability (CC β ) and ruggedness of the method has been reported. The results of the validation process demonstrate the agreement of the method with the provisions of Commission Regulation 401/2006/EC. The mean recovery calculated at three levels of fortification (0.5, 1.0, and 1.5-fold the MRL) was 91% and the maximum relative standard deviation value for the within-laboratory reproducibility was 15%. Limit of detection (LOD) and limit of quantitation (LOQ) values were 0.006 g kg −1 and 0.015 g kg −1 while the CC α and CC β values were 0.058 g kg −1 and 0.065 g kg −1 , respectively. The relative expanded measurement uncertainty of the method was 7%. The method was not affected by slight variations of some critical factors (ruggedness minor changes) as pre-treatment and clean-up of milk samples, thermal treatment and different storage conditions, as well as by major changes valued in terms of milk produced by different species (buffalo, goat and sheep). The method allowed accurate confirmation analyses of milk samples, resulted positive by the screening method. In fact, the Z-score values attained in a proficiency test round were well below the reference value of 1, proving the excellent laboratory performances.

This paper proposes a new template matching method that is robust to outliers and fast enough for real-time operation. The template and image are densely transformed in binary code form by projecting and quantizing histograms of oriented gradients. The binary codes are matched by a generic method of robust similarity applicable to additive match measures, such as L p -and Hamming distances. The robust similarity map is computed efficiently via a proposed Inverted Location Index structure that stores pixel locations indexed by their values. The method is experimentally justified in large image patch datasets. Challenging applications, such as intra-category object detection, object tracking, and multimodal image matching are demonstrated.

Racehorses given a slurry of sodium bicarbonate (known colloquially as a 'milkshake') before a race have elevated concentrations of carbon dioxide in their blood. Racing administrators have reacted to this attempt to enhance the performance of the animal by setting limits to 'total carbon dioxide' (TCO2, the sum of carbon dioxide, carbonic acid, carbonate and bicarbonate) in prerace samples of plasma. The threshold limit for TCO2 in the rules of racing is an amount concentration of 36.0 mmol/L, with further action ensuing if the reported concentration is greater than an action limit that is calculated from the knowledge of the measurement uncertainty. At present in Australia, the action limit is 37.0 mmol/L, which is based on a combined standard measurement uncertainty of 0.22 mmol/L. From data obtained in a 1997 study in 515 normal racehorses, we have established the distribution (as a probability density function, PDF) of TCO2. This is combined with data from Australian laboratories of 126 horses that were tested following a positive screen, out of which 78 were confirmed positive. We employ the maximum entropy method to establish the PDFs and then apply Bayes Theorem to answer the question 'given the measured TCO2 concentration what is the probability that a horse has been administered bicarbonate'? The distributions are not normal, which precludes simple approaches that calculate standard deviations from the data. For an action level of 37.0 mmol/L, there is a chance of only 1 in 2 020 000 that a nondoped horse will be judged to be doped, which implies this present threshold is unlikely to lead to conviction of an innocent trainer.

In this paper, we present complex permittivity data at microwave frequencies (approximately 10 GHz) for many common plastics over a temperature range of 122 to 375 K. The measurements were made with a TE 01 dielectric resonator placed inside an environmental chamber. Data are presented for the following materials: acrylonitrile butadiene styrene, polytetrafluoroethylene, cross-linked polystyrene, tetrafluorethylene-perfluorpropylene, polypropylene, polysulfone, polymethylmethacrylate, polyvinyl chloride, polycarbonate, high-density polyethylene, polyoxy-methylene (acetal homopolymer), and polyamide.

The objective of this research was to test suitability of the Dumas combustion method to completely substitute the Kjeldahl method in routine laboratory determination of crude protein content in cereals and oilseeds. The validation of the method demonstrated that it is able to determine crude protein content in cereals and oilseeds in an efficient and accurate manner, with a detection

Uncertainty of a measurement result is a major issue in all fields of measurement. Weighing is a critical step in any chemical laboratory and analytical methods. It&#x27;s an important uncertainty sources in uncertainties measurement in an analysis. In this paper we tried to present the influence factors that affect in uncertainty measurement of a mass determination. Technical specifications of a balance such as: Readability, Repeatability, Non-linearity, Sensitivity Tolerance, Temperature Coefficient of Sensitivity and effects of environmental factors such as: air humidity, air pressure and air buoyancy were estimated. In the absence of some disturbance factor like water adsorption phenomena, evaporation, magnetic and electrostatic effects, the measurement uncertainty for an electronic balance in our laboratory is in the 10-4 to 10-3 range (100 to 1000 ppm).

In this report a gravimetric micro-Winkler titration method for determination of dissolved oxygen concentration in water is presented. Mathematical model of the method taking into account all influence factors is derived and an uncertainty analysis is carried out to determine the uncertainty contributions of all influence factors. The method is highly accurate: the relative expanded uncertainties (k = 2) are around 1% in the case of small (9-10 g) water samples. The uncertainty analysis carried out in characterizing the uncertainty of the method is the most comprehensive published for a micro-Winkler method, resulting in experimentally obtained estimates for all uncertainty sources of practical significance (around 20 uncertainty sources altogether).