Search Results (55)

This paper addresses steady-state visually evoked potential (SSVEP) classification in wearable extended-reality (XR) brain–computer interfaces (BCIs), with a threefold objective. First, it investigates the effectiveness of deep learning (DL)-based SSVEP classification under XR stimulation, where platform-dependent rendering, optical see-through visualization, reduced luminance contrast, and interaction with the real environment may degrade the quality of the elicited EEG response. Second, a metrology-based performance assessment is proposed according to the Guide to the Expression of Uncertainty in Measurement (GUM), with classification accuracy and information transfer rate (ITR) expressed as best estimates with associated standard uncertainties. Finally, EEG channel reduction is analyzed toward lightweight XR-SSVEP implementations. As a representative SSVEP-specific DL model, the SSVEP time-frequency fusion network (SSVEP-TFFNet) is evaluated on an open XR benchmark dataset comprising 30 subjects and 1200 trials acquired using Microsoft HoloLens 2. A subject-independent comparison with filter-bank canonical correlation analysis (FBCCA) is performed, while intra- and inter-subject variability are incorporated into the uncertainty evaluation. Results show that SSVEP-TFFNet outperforms FBCCA under the considered XR conditions. Moreover, reduced 6- and 4-channel configurations preserve performance close to the full 8-channel montage. These findings provide evidence of the potential of suitably selected DL models for XR-based SSVEP classification and support uncertainty-aware, reduced-electrode wearable implementations. Full article

Accurate and traceable attenuation measurements are essential for RF instrumentation, communication equipment, electromagnetic compatibility (EMC) testing, and wide dynamic-range signal characterization. This paper presents a practical, accurate, and robust working-standard attenuation measurement system covering the frequency range from 9 kHz to 10 MHz for traceable RF attenuation calibration and wide dynamic-range characterization. The system is based on a direct RF substitution technique and employs two cascaded resistive step attenuators with 10 dB and 1 dB step sizes as the reference standard, providing a total attenuation range of 60 dB with 1 dB resolution. A general-purpose receiver is used as a precision level detector, enabling a simple and fully automated measurement configuration. Traceability is established through calibration against an inductive voltage divider (IVD)-based primary attenuation standard. Owing to the excellent frequency flatness of the reference standard, a single-frequency calibration at 1 MHz is sufficient to characterize the entire operating range from 9 kHz to 10 MHz. The direct measurement capability extends to 60 dB and is further expanded beyond 100 dB through a double-step measurement technique. A comprehensive uncertainty evaluation in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM) yields expanded uncertainties of 3.6 × 10⁻³ dB at 20 dB, 5.6 × 10⁻³ dB at 60 dB, and 8.4 × 10⁻³ dB at 100 dB. Measurements up to 60 dB show excellent agreement with the primary attenuation standard, while alternative validation demonstrates consistency at 80 dB and 100 dB. The obtained uncertainty levels are comparable to or lower than those reported for similar systems in the literature. The proposed system provides a practical and traceable solution for routine RF attenuation calibration, supporting EMC testing, communication-system characterization, RF sensing and measurement applications, and the dissemination of RF metrological traceability. Full article

An interlaboratory comparison of RF power measurements using automatic power measurement software was carried out among partners of the European Partnership on Metrology project titled “Development of RF and microwave metrology capability II” (RFMicrowave2). The absolute RF power output of a travelling signal generator was measured at six frequencies between 2 GHz and 18 GHz and at three nominal power levels of −10 dBm, 0 dBm, and 10 dBm. Comparison results were evaluated in terms of comparison reference values, degrees of equivalence, and normalised errors. Uncertainty evaluations were performed using both the Guide to the Expression of Uncertainty in Measurement and Monte Carlo simulation methods. The results demonstrate an acceptable level of agreement among participating laboratories and confirm the applicability of automatic power measurement software for interlaboratory RF power comparisons. Full article

We present a Fourier-transform (FT)-based framework for quantitative analysis of whispering gallery mode (WGM) spectra in soft photonic microcavities. By treating the WGM spectrum as a quasi-periodic signal, the method enables robust extraction of the optical path length $L_{\mathrm{opt}}={\lambda }_c^2/\Delta \lambda$ directly in the frequency domain, avoiding explicit peak identification and reducing sensitivity to background and spectral overlap. This quantity is used as a primary measurand within a unified metrological formulation: when the cavity radius R is known, it yields the effective refractive index $n_{\mathrm{eff}}=L_{\mathrm{opt}}/\left(2\pi R\right)$; when the refractive index n is known, it provides an inferred geometric path length $l_{\mathrm{geo}}=L_{\mathrm{opt}}/n$. Following the Guide to the Expression of Uncertainty in Measurement (GUM), we establish the measurement models and evaluate the uncertainty budget, identifying the FSR determination as the dominant contribution (relative uncertainty $7.7\%$), with secondary contributions from radius measurement ($1.5\%$) and negligible influence from wavelength calibration. The framework is applied to two representative soft photonic systems as complementary test and consistency cases. For Rhodamine B-doped mesoporous silica microcapsules ($R=44 \mu \mathrm{m}$), we obtain $n_{\mathrm{eff}}=1.164\pm 0.09$, corresponding to a porosity of $63.3\%$ via Bruggeman effective medium theory, in close agreement with independent BET measurements ($62.8\%$). For surfactant-stabilized Rhodamine 640-doped benzyl alcohol microdroplets, the method identifies dominant Fourier-domain periodicities and yields inferred geometric path lengths consistent with near-equatorial mode propagation. An additional $N=14$ droplet analysis gives an FT-inferred radius of $60.78\pm 1.91 \mu \mathrm{m}$, in close agreement with the microscopy-estimated radius of approximately $60 \mu \mathrm{m}$. By combining Fourier-domain analysis with explicit measurement modeling and uncertainty quantification, this work establishes FT-WGM spectroscopy as a reproducible and generalizable tool for single-particle metrology in complex soft-matter microcavities. Full article

Raman Distributed Temperature Sensing (DTS) provides spatially distributed temperature measurements along optical fibers and is increasingly used for monitoring large-scale infrastructures and experimental facilities, enabling three-dimensional reconstruction of temperature fields. However, such measurements involve specific implementation constraints and may be affected by significant errors, with uncertainties influenced by factors such as calibration, environmental conditions, spatial resolution effects, and fiber positioning. Ensuring the metrological validity of Raman-based DTS measurements therefore requires a rigorous quantification of the associated measurement uncertainties. In this work, a complete uncertainty analysis of Raman-based DTS measurements is performed following the principles of the Guide to the Expression of Uncertainty in Measurement (GUM). A measurement model describing the relationship between Raman backscattered signals and temperature is established, and all relevant uncertainty sources are identified and quantified. The methodology is applied to a full-scale experimental facility equipped with a DTS interrogator and a dedicated calibration setup. Uncertainty propagation is performed using both first-order Taylor series expansion and Monte Carlo simulation, providing consistent results. The analysis shows that calibration uncertainty, spatial dispersion of the temperature field and fiber positioning within the reconstructed temperature field represent the dominant contributions to the combined uncertainty. The proposed approach provides a rigorous framework for the metrological qualification of Raman DTS systems and offers practical guidance for improving measurement reliability in distributed temperature monitoring applications. Full article

Fracture toughness is a very important mechanical attribute that affects the strength of rail steel used in high-speed rail systems. This study tests the measurement uncertainty that comes with measuring the plane strain fracture toughness (K_IC) of R350HT rail steel. We used the Single-Edge Bend (SEB) specimen to do fracture toughness testing. We used the Guide to Expressing Measurement Uncertainty (GUM)-based method to figure out how much uncertainty came from measuring the load, the crack opening displacement (COD), and the specimen’s shape and figuring out the crack length. At a 95% confidence level (k = 2), the combined standard uncertainty was found to be 0.881 MPa·m^1/2, which is the same as an expanded uncertainty of 1.761 MPa·m^1/2. The measured fracture toughness value of 40.59 ± 1.76 MPa·m^1/2 meets the standards for rail steels. The results show how important it is to include measurement uncertainty in conformity assessment methods for safety-critical railway components. They also provide an experimentally proven framework for accurate mechanical property evaluation. Full article

Measurement models that have a chemical composition as one of the arguments require special attention when used with the law of propagation of uncertainty from the Guide to the expression of uncertainty in measurement. The constraint that the amount fractions in a composition add exactly to unity not only affects the covariance matrix associated with the composition, but also impacts the differentiation of the measurement model to obtain the expressions and values of the sensitivity coefficients. Differentiating the measurement model with respect to each variable individually is not possible as it involves evaluating the model for infeasible inputs, leading to an undefined output. In this work, a numerical method for constrained partial differentiation is presented, enabling the use of the law of propagation of uncertainty for measurement models with compositions as one of their arguments. The numerical method enables treating the measurement model as a black box and using it with measurement models in the form of an algorithm. The numerical method is demonstrated by showing how the uncertainty associated with composition, temperature and pressure can be propagated through an equation of state, in this case, the GERG-2008 equation of state. It is shown that this differentiation can be completed in a few simple steps, requiring only a valid implementation of the measurement model that provides an output value for given input quantities. The numerical differentiation method applies in principle to all differentiable functions of a composition. Full article

The characterization of mechanical properties in heat-treated carbon steels, which is crucial for quality control, traditionally relies on destructive testing. This study evaluated the reliability of the non-destructive ultrasonic technique as a metrological alternative for AISI 1045 steel. Samples subjected to six heat treatment conditions (Annealing, Normalizing, Quenching, and Tempering) were characterized by hardness, metallography, and ultrasound. Through linear regression analyses, the multiparametric model combining sound velocity, attenuation, and FWHM demonstrated exceptional metrological precision, resulting in a coefficient of determination of (R² = 96.687%). The metrological robustness of the model was validated by quantifying the Expanded Uncertainty (U), following the GUM (Guide to the Expression of Uncertainty in Measurement). It is concluded that the multiparametric ultrasonic methodology is an accurate, robust, and non-destructive alternative for the quantitative determination of Vickers Hardness in AISI 1045 steels, contributing to the optimization of industrial processes and metrological rigor. Full article

In digital-measurement-assisted assembly of large aircraft components, the spatial layout of Enhanced Reference System (ERS) points determines coordinate transformation accuracy and stability. To address manual layout limitations—specifically low efficiency, occlusion susceptibility, and physical deployment limitations—this paper proposes an adaptive planning method under engineering constraints. First, based on the Guide to the Expression of Uncertainty in Measurement (GUM) and weighted least squares, an analytical transformation sensitivity model is constructed. Subsequently, a multi-scale sample library generated via Monte Carlo sampling trains a high-precision BP neural network surrogate model, enabling millisecond-level sensitivity prediction. Combining this with ray-tracing occlusion detection, a weighted genetic algorithm optimizes transformation sensitivity, spatial uniformity, and station distance within feasible ground and tooling regions. Experimental results indicate that the method effectively avoids occlusion. Specifically, the Registration-Induced Error (RIE) is controlled at approximately 0.002 mm, and the Registration-Induced Loss Ratio (RILR) is maintained at about 10%. Crucially, comparative verification reveals an RIE reduction of approximately 40% compared to a feasible uniform baseline, proving that physics-based data-driven optimization yields superior accuracy over intuitive geometric distribution. By ensuring strict adherence to engineering constraints, this method offers a reliable solution that significantly enhances measurement reliability, providing solid theoretical support for automated digital twin construction. Full article

Background: Measurement uncertainty (MU) is a crucial parameter for ensuring the reliability of analytical methods and the validity of results, as required by ISO 17025:2017. Its estimation is particularly critical for quality control laboratories, where compliance decisions are based on a rigorous interpretation of uncertainties. Methods: In this study, we evaluated the uncertainty associated with an HPLC-UV method for the determination of Metopimazine (MPZ) in a pharmaceutical form, applying two complementary approaches: The ISO-GUM (Guide to the Expression of Uncertainty in Measurement) top-down approach and the Monte Carlo Simulation (MCS). Results: The results of both approaches showed excellent agreement, thus validating the robustness of the evaluation. The analysis of uncertainty sources revealed that the accuracy of the sample volume (V_Sample) and the calibration standard (C_x) were the dominant contributors, representing 39.9% and 36.2% of the total uncertainty, respectively. Combined, these two factors accounted for 76.1% of the variability, underscoring their critical impact on the assay’s precision. The expanded uncertainty (k = 2, 95% confidence level) was determined to be (99.41 ± 0.69)%, reflecting the method’s reproducibility. Conclusions: These results highlight the importance of rigorously controlling calibration standard preparation, sample volume, and repeatability conditions to optimize the reliability of the assay. Full article

Most flow metering methods used in industrial applications produce results sensitive to the local velocity profile. In response, manufacturers often implement correction algorithms; however, these are rarely supported by rigorous uncertainty evaluations. This paper presents a Reynolds number-dependent velocity profile correction, applicable under fully developed flow conditions and for the Reynolds-dependent part of the correction in disturbed flows, demonstrated on the example of an ultrasonic clamp-on flow meter. Measurement uncertainties are evaluated and propagated through a regression model using Monte Carlo simulation, in compliance with the Guide to the Expression of Uncertainty in Measurement (GUM). Special care is taken to assess the validity range and impact of assuming fully developed flow conditions at the test rig. A validation case demonstrates the reliability of the correction algorithm and its associated uncertainty within the tested conditions. The proposed approach is applicable to other meter types and can be extended to corrections for specific flow disturbances. Full article

Accurate electric current measurement is fundamental to the safe and efficient operation of modern power systems. Current transformers (CTs), which serve as a critical interface between high-voltage power networks and measuring or protection devices, are susceptible to various errors and uncertainties that can significantly impact the reliability of measurement results. This article provides a critical and comprehensive review of the current literature concerning the types and causes of errors in CTs, with particular emphasis on current ratio error and phase displacement. Special attention is given to the role of international standards in defining accuracy classes and permissible error limits. Methods for evaluating measurement uncertainty are also discussed, in accordance with the guidelines outlined in the Guide to the Expression of Uncertainty in Measurement (GUM), highlighting their decisive impact on the credibility of measurement results. Modern approaches—such as the application of artificial intelligence in estimating measurement errors—are also considered. This review serves as a comprehensive resource for engineers, metrologists, and researchers seeking to enhance the accuracy of CTs, particularly in measurement and protection applications. Full article

Odorous emissions from hot-mix asphalt (HMA) plants are a growing environmental concern, particularly due to airborne aldehydes and ketones, which have low odor thresholds and a strong sensory impact. This study presents a field-ready analytical method for monitoring odor-active volatile compounds. The system uses dynamic solid-phase microextraction (SPME and SPME Arrow) with on-fiber derivatization via O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine (PFBHA) and is coupled to gas chromatography–mass spectrometry (GC–MS) for direct detection. A flow-cell sampling unit enables the real-time capture of aliphatic aldehydes and ketones under transient emission conditions. Calibration using permeation tubes demonstrated sensitivity (limits of detection (LODs) below 0.13 μg/m³), recovery above 85% and consistent reproducibility. Compound identity was confirmed using retention indices and fragmentation patterns. Uncertainty assessment followed ISO GUM (Guide to the Expression of Uncertainty in Measurement) standards, thereby validating the method’s environmental applicability. Field deployment 200 m from an HMA facility identified measurable concentrations that aligned with CALPUFF model predictions. The method’s dual-isomer resolution and 10 min runtime make it ideal for responding to time-sensitive odor complaints. Overall, this approach supports regulatory efforts by enabling high-throughput on-site chemical monitoring and improving source attribution in cases of odor nuisance. Full article

In response to the demand for precise measurement of illuminance distribution in the quality control of LED monitoring fill light products and the iterative direction of secondary optical design, distributed photometric sensors have shown advantages, but their measurement uncertainty assessment faces challenges. This paper addresses the problem of uncertainty evaluation in photometric parameter measurement with a two-dimensional horizontal distributed photometric sensor and proposes an uncertainty evaluation framework for this task. We have established an uncertainty analysis model for the measurement system and provided two uncertainty synthesis methods, The Guide to the Expression of Uncertainty in Measurement and the Monte Carlo method. This study designed illuminance measurement experiments to validate the feasibility of the proposed uncertainty evaluation method. The results demonstrate that the actual probability distribution of the measurement data follows a trapezoidal distribution. Furthermore, the expanded uncertainty calculated using the GUM method was 21.1% higher than that obtained by the MCM. This work effectively addresses the uncertainty evaluation challenge for illuminance measurement tasks using a two-dimensional horizontal distributed photometric sensor. The findings offer valuable reference for the uncertainty assessment of other high-precision optical instruments and possess significant engineering value in enhancing the reliability of optical metrology systems. Full article

This study aims to develop a framework for evaluating the uncertainty of a surface image velocimeter (SIV) based on the Guide to the Expression of Uncertainty in Measurement (GUM) standard. To achieve this, the uncertainty factors of the SIV were thoroughly reviewed and categorized into those that can be directly incorporated into the functional equation for surface velocity calculation and those that cannot. Factors that can be included in the velocity calculation equation primarily involve image displacement measurement and the accurate determination of the time interval between successive stationary images. Conversely, parameters and image quality were identified as uncertainty factors that are not directly integrated into the velocity calculation equation. Based on the GUM standard, equations for calculating the uncertainty of surface velocity, depth-averaged velocity, and flow discharge measurements were developed. Furthermore, using the results from the standard uncertainty evaluation, assessments were performed for the velocity uncertainty of both surface velocity and depth-averaged velocity, as well as the flow rate measurement uncertainty of the SIV. We anticipate that the velocity and flow rate measurement uncertainty framework and the uncertainty analysis results for the SIV presented in this research will enhance the reliability of SIV-derived flow rate measurements, thereby contributing to more dependable flow rate determination. Full article