Systematic Measurement Errors Research Articles

Kinematic calibration of a 5-DOF hybrid machining robot using an extended Kalman filter method

This paper focuses on kinematic calibration of a novel 5-DOF hybrid robot and attention is paid to the suppression of ‘observation noise’ impact caused by the measurement system and unconsidered source errors. The proposed method that is pertinently developed to improve the accuracy of the targeted robot, is implemented as follows: with the aid of screw theory, a linear map between the pose error twist of the end effector and all possible geometric source errors of the hybrid machining robot is formulated. Following the measurement and solution of pose error twist, an extended Kalman filter (EKF) is then employed to obtain more reliable and stable identification results of geometric errors. A linearized error compensator is then proposed and used in calibration experiments. Compared with the least square method, the proposed EKF method is proved to be robust and has good compensation effect in the verification configurations. After kinematic calibration, the positional and angular errors of the robot are reduced to be less than 60.6 μm and 67.6 μrad respectively. The results verify the effectiveness and general applicability of the proposed identification and compensation strategy.

Measurement error in echocardiographic assessment of aortic stenosis: an epidemiological consideration of research methodology and clinical practice

Abstract Background/Introduction Current international guidelines on treatment of valvular heart disease contain recommendations for aortic valve replacement based exclusively on abnormal echocardiographic parameters in asymptomatic patients with aortic stenosis (AS). To prevent misclassification and subsequent mistreatment of patients, these recommendations require accurate and unbiased measurements of hemodynamic parameters. Purpose To illustrate consideration and impact of measurement error in echocardiographic assessment of aortic stenosis in both the research and clinical setting. Methods First, a systematic review was performed to investigate the recognition of and correction for measurement error in clinical studies on the prognostic value of peak aortic jet velocity (Vmax), mean pressure gradient (MPG), and effective orifice area (EOA). Second, all potential erroneous sources in the calculation of those primary parameters were listed stratified to random or systematic measurement error, and subsequently their magnitude was quantified. Third, the impact of various types of measurement error on current thresholds for intervention was graphically illustrated in different clinical scenarios. Results The presence of measurement error was acknowledged in 44% of the 36 included studies, while none utilized methods to correct for it. Interobserver variability ranged between 0.9–8.3% for Vmax and MPG but was substantially higher for EOA (range 7.7–12.7%) implying lower reliability (Figure 1). Furthermore, the invalid assumption of a circular left ventricular outflow tract area resulted in a median underestimation in EOA of 22.5% compared to 3D-transesophageal echocardiography (3D-TEE), computed tomography (CT), and cardiovascular magnetic resonance (CMR) planimetry. Figure 2 illustrates the impact of this discrepancy on the classification of AS using one-sided t-tests to determine the areas under the curve; the proportion of patients with non-severe AS in a hypothetical cohort (based on values from the PARTNER 3 trial [1[) increased by 42%. Conclusion(s) Measurement error is underrecognized in studies of echocardiographic assessment of aortic stenosis. This review demonstrates that random and systematic measurement errors affect echocardiographic assessment, leading to potential misdiagnosis and subsequent mistreatment. Clinicians and scientists should be aware of the implications of measurement errors to enhance rightful clinical decision-making and assure research validity. Funding Acknowledgement Type of funding sources: None.

Mismeasurement and efficiency estimates: Evidence from smallholder survey data in Africa

AbstractSmallholder agriculture in sub‐Saharan Africa is commonly characterised by high levels of technical inefficiency. However, much of this characterisation relies on self‐reported input and production data, which are prone to systematic measurement error. We show theoretically that non‐classical measurement error introduces multiple identification challenges and sources of bias in estimating smallholders' technical inefficiency. We then empirically examine the implications of measurement error for the estimation of technical inefficiency using smallholder farm survey data from Ethiopia, Malawi, Nigeria and Tanzania. We find that measurement error in agricultural input and production data leads to a substantial upward bias in technical inefficiency estimates (by up to 85% for some farmers). Our results suggest that existing estimates of technical efficiency in sub‐Saharan Africa may be severe underestimates of smallholders' actual efficiency and what is commonly attributed to farmer inefficiency may be an artefact of mismeasurement in agricultural data. Our results raise questions about the received wisdom on African smallholders' production efficiency and prior estimates of the productivity of agricultural inputs. Improving the measurement of agricultural data can improve our understanding of smallholders' production efficiencies and improve the targeting of productivity‐enhancing technologies.

Liquid-phase temperature in the SpraySyn flame measured by two-color laser-induced fluorescence thermometry and simulated by LES

In the SpraySyn burner (Schneider et al., 2019) a solution of metal salts in a combustible liquid is atomized in a two-fluid nozzle with molecular oxygen as dispersion gas to generate oxide nanoparticles via combustion synthesis. The flame is anchored by a methane (CH4)/oxygen (O2) premixed flat flame stabilized on a porous plate surrounding the spray nozzle. This burner features a standardized design with simple geometry, which provides well-defined boundary conditions for the simulation to support model development and the interaction between experiment and simulation. In this work, two-color laser-induced fluorescence (2cLIF) thermometry based on the fluorescence tracer coumarin 152 dissolved in ethanol is applied to provide temporally averaged but spatially resolved liquid-phase temperature maps. The operating conditions for the spray formation were modified by varying the injection rate and the dispersion gas flow. Liquid-phase temperatures were predicted by large-eddy simulation (LES), where the spray is modeled by a Eulerian-Lagrangian approach based on measured liquid droplet properties (initial liquid-phase temperature, droplet size, and velocity distribution). Droplet size and velocity were measured by phase-Doppler anemometry (PDA). Gas-phase turbulent combustion is modeled with the flamelet-generated manifold (FGM) approach. Droplet temperature distributions were provided by the simulation to assess the systematic measurement error caused by LIF-signal averaging. Experimental and simulated average liquid-phase temperature maps are compared. The simulation results were found to be in good agreement with the experiment by showing a suitable prediction of the droplet heat-up process within the experimentally probed spray region.

Linkage of the nationally representative Canadian Community Health Survey - Nutrition 2004 to routinely collected mortality records.

The Canadian Community Health Survey (CCHS) - Nutrition 2004 (n=35,107; interview dates from January 2004 to January 2005) linked to the Canadian Vital Statistics - Death Database (CVSD) (2011) represents a novel linkage of a population-based, nationally representative nutrition survey with routinely collected mortality records (including date and cause of death). The linkage was done through individual tax data in Canada, and contains longitudinal records for 29,897 Canadians aged 0 years and older-1,753 of whom died-in the 10 provinces of Canada. The median follow-up time was 7.49 years, with 102,953 person-years among males and 114,876 person-years among females (unweighted), and included a special sampling survey weight (for linked data) to account for those who did not agree to share and link their information. The CCHS - Nutrition 2004 linked to CVSD has been used to evaluate associations between lifestyle and sociodemographic characteristics and mortality. Using these data, statistical methods have been developed and tested to control random and systematic measurement errors when evaluating the relationship between different dietary exposures (evaluated using repeated 24-hour dietary recalls) and health outcomes. The linked data are available through Statistics Canada's Research Data Centres.

Thermal Property Analysis of Precision Machinery and Its Thermal Error Compensation

The machining error caused by the thermal deformation of machines or tools accounts for half or even more in the total error, and the machining precision could be improved by stabilizing the heat balance of the process system. However, few of the existing studies have concerned about the thermal deformation law caused by the high-speed self-feed spindle system that could meet the performance requirements of high-speed cutting in precision machining, therefore, it’s of great necessity to study the thermal properties of precision machinery. For this reason, this paper took the precision machinery with a high-speed self-feed spindle system as the subject to study its thermal properties and thermal error compensation. At first, this paper introduced the composition of the precision machining control system and analyzed the thermal properties of the subject. Then, the heat source and heat exchange forms of the precision machinery were analyzed, the thermal intensity of the internal and external heat sources during the machining process was calculated, and the corresponding thermal boundary conditions were given. After that, this paper divided the heat sources of the subject during high-speed cutting into two types: internal heat source and external environment heat source, and carried out analysis. Moreover, this paper gave the structure of a thermal error and temperature synchronous measurement system for precision machinery, integrated the features of the thermal error data of two groups of high-speed cutting process, and built a thermal error compensation model based on the Bayesian network. At last, experimental results verified the effectiveness of the model.

Associations between dietary patterns and cardiovascular disease risk in Canadian adults: a comparison of partial least squares, reduced rank regression and the simplified dietary pattern technique.

ObjectivesWe aimed to compare two data reduction techniques, partial least squares (PLS) and reduced rank regression (RRR), in identifying dietary patterns associated with a high cardiovascular disease (CVD) risk in Canadian adults, and to construct PLS- and RRR-based simplified dietary patterns as well as evaluating associations between derived patterns and CVD risk.
 ApproachData were collected from 24-hour dietary recalls of adult respondents in two cycles of the nationally representative Canadian Community Health Survey (CCHS)-Nutrition: CCHS 2004 linked to health administrative databases (n = 12,313) and CCHS 2015 (n = 14,020). Using 39 food groups, PLS and RRR were applied for the identification of an energy-dense (ED), high-saturated-fat (HSF) and low-fiber-density (LFD) dietary pattern. Associations of derived dietary patterns with lifestyle characteristics and CVD incidence and mortality were examined using weighted multivariate regression and weighted multivariable-adjusted Cox-proportional hazard models, respectively. Random and systematic measurement errors were adjusted for in all statistical analyses.
 ResultsPLS and RRR identified highly similar ED, HSF, LFD dietary patterns with common high positive loadings for fast food, carbonated drinks, salty snacks and solid fats, and high negative loadings for fruit, dark green vegetables, red and orange vegetables, other vegetables, whole grains, legumes and soy (≥|0.17|). Food groups with the highest loadings were summed to form simplified pattern scores. Although the dietary patterns were not significantly associated with CVD risk, they were positively associated with 402 kcal/d higher energy intake (P-trends <0.05) and higher obesity risk [PLS (OR: 2.09; 95% CI: 1.62, 2.7) and RRR (OR: 1.76; 95% CI: 1.44, 2.17)] (P-trends <0.0001) in the fourth quartiles as compared to the first.
 ConclusionPLS and RRR were shown to be equally effective for derivation of a high-CVD-risk dietary pattern among Canadian adults. This research highlights the importance of leveraging linked data to inform public health nutrition policies. Further research is warranted on the role of major dietary components in cardiovascular health.

Performance Evaluation and Requirement Analysis for Chronometric Leveling with High-Accuracy Optical Clocks

The high-precision unification of global height datum has long been a hot issue in the field of geodesy. The chronometric leveling method originates from the gravitational redshift effect of general relativity, which may provide a new solution for the unification of global height datum. The height difference between the two locations could be measured via the frequency comparison of high-precision optical clocks. We build the error model for chronometric leveling, mainly including the measurement systematic error of two optical clocks, frequency statistical error of two optical clocks, and transmission path error of optical fiber when using optical fiber as carrier. Then, we put forward the schemes to achieve chronometric leveling. The performance of the height measurement using different schemes is evaluated. Additionally, considering the requirements of geodesy, four typical height measurement accuracy factors for chronometric leveling are proposed. Meanwhile, the corresponding accuracy requirements for optical clocks and frequency transmission techniques are also given. It has important guiding significance for the unification of the global height datum and related geoscience fields using high-accuracy chronometric leveling in the future.

Probing the dark photon via polarized DIS scattering at the HERA and EIC

The dark photon is widely predicted in many new physics beyond the Standard Model. In this work, we propose to utilize the polarized lepton cross section and single-spin asymmetry in neutral current DIS process at the HERA and upcoming Electron-Ion Collider (EIC) to probe the properties of the dark photon. It shows that we can constrain the mixing parameter ϵ<0.02 when the dark photon mass mAD<10GeV at the HERA with polarized lepton beam and this bound is comparable to the limit from the unpolarized data of HERA I and II. With the help of high integrated luminosity and high electron beam polarization of the EIC, the upper limit of the ϵ could be further improved. Depending on the assumption of the systematic error of the cross section measurements, we obtain ϵ<0.01∼0.02 for the mass region mAD<10GeV under the integrated luminosity of 300fb−1. A similar and robust upper limit for the ϵ could be obtained from the single-spin asymmetry measurement, which is not depending on the assumption of the systematic errors.

Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

We constrain cosmological and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey Year-3 data. We describe our modeling framework, and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy bias model and redMaGiC galaxy sample, we obtain constraints on the matter density to be $\Omega_{\rm m} = 0.325^{+0.033}_{-0.034}$. We also implement a non-linear galaxy bias model to probe smaller scales that includes parameterization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate the stability of the constraints to changes in the theoretical model. Using the redMaGiC galaxy sample as foreground lens galaxies, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to de-correlation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the $S_8$ parameter. We find that a scale-, redshift- and sky-area-independent phenomenological de-correlation parameter can effectively capture the impact of this systematic error. We trace the source of this de-correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the $S_8$ parameter are consistent with previous studies, and we find a small shift in the $\Omega_{\rm m}$ constraints compared to the fiducial redMaGiC sample. We constrain the mean host halo mass of the redMaGiC galaxies in this new sample to be approximately $1.6 \times 10^{13} M_{\odot}/h$.

Algorithm for ionosphere delay computation based on Klobuchar-like coefficients for regional navigation satellite system users

The ionospheric effect on radio wave propagation error has a significant impact on navigation, positioning, and real-time measurements. It is the primary source of errors in high precision aviation and measurement systems. A set of eight coefficients is used to correct ionospheric errors for Indian Regional Navigation Satellite System (IRNSS) users. Currently, the Klobuchar model is an effective low computational mathematical model for ionospheric range error mitigation through a set of eight coefficients. It has low accuracy in Equatorial Ionization Anomaly (EIA) regions and can correct up to ∼60% of the ionospheric range error. This paper proposes an ionospheric error correction model that can be applied to such measurements as well as an associated error model to compute accuracy with a differential interval of observations 5 m, 30 m and 60 m. The numerical simulation results show that compared to widely used algorithms, the proposed strategy can enhance the 83.13% ionospheric correction with Klobuchar- like coefficients at a sampling rate of 5 m. The proposed solution could be effective for Regional Navigational Satellite Systems (RNSS) for ionospheric delay corrections in low-latitude regions.

Using Controlled Feeding Study for Biomarker Development in Regression Calibration for Disease Association Estimation.

Correction for systematic measurement error in self-reported data is an important challenge in association studies of dietary intake and chronic disease risk. The regression calibration method has been used for this purpose when an objectively measured biomarker is available. However, a big limitation of the regression calibration method is that biomarkers have only been developed for a few dietary components. We propose new methods to use controlled feeding studies to develop valid biomarkers for many more dietary components and to estimate the diet disease associations. Asymptotic distribution theory for the proposed estimators is derived. Extensive simulation is performed to study the finite sample performance of the proposed estimators. We applied our method to examine the associations between the sodium/potassium intake ratio and cardiovascular disease incidence using the Women's Health Initiative cohort data. We discovered positive associations between sodium/potassium ratio and the risks of coronary heart disease, nonfatal myocardial infarction, coronary death, ischemic stroke, and total cardiovascular disease.

Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women

The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020). Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

A Data Driven Approach for Monitoring Puncture Events in Capacitor Voltage Transformers

In 2014 a number of Capacitor Voltage Transformers (CVTs) exploded in the Swedish transmission grid. To address this problem, data driven methods for continuously monitoring CVTs were developed. Thanks to these methods, CVT capacitor punctures are now regularly noticed and addressed before causing serious damage. This paper describes the algorithms used to make this possible. Detecting all CVT capacitor punctures as they occur increases the transmission system stability, avoids equipment damage, lowers risks to personnel when visiting the substations and makes it possible to correct measurement errors in the energy measurement systems. Automatic supervision scripts, using energy meter data, are running continuously and will alert the service personal immediately when problems occur. With the algorithms proposed in this article, the Swedish National Grid (Svk) has detected many old punctures and expects no future capacitor punctures to go undetected. Detecting all new punctures enables Svk to save substantial future cost since planned actions now are possible.

Differentiating analytical error from sampling errors in PAT methods through variographic analysis

In variographic analysis the nugget effect provides an estimate of the total process measurement system error. The value of variographic analysis can be further increased by differentiating the analytical error from the sampling errors. The ratio of the minimum practical error (MPE) to the analytical error provides an estimate of the suitability and performance of a sampling system since the analytical error would still remain even if sampling errors could be completely eliminated. The sampling and analytical errors for four systems used to obtain 1-D lots of pharmaceutical powder blends is presented. The first studies were conducted with blends moving over a conveyor belt and with the feed-frame of a tablet press. The researchers then developed and patented a new stream sampler and chute for sampling and analysis of pharmaceutical powder blends. Near Infrared or Raman spectra were obtained as the powder blends flowed or moved and used to determine the drug concentration in the blends. Even though these methods do not require sample extraction and sample preparation in a laboratory, they are still subject to sampling errors which were estimated through the variographic analysis. The MPE was compared to the analytical error for these four systems. The results obtained show that it is often possible to reduce sampling errors to less than ten times the analytical error. These studies represent the first efforts to estimate and reduce sampling errors in the analysis of the powder blends used to manufacture the tablets that many patients take daily.

A measurement of stellar surface gravity hidden in radial velocity differences of comoving stars

ABSTRACT The gravitational redshift induced by stellar surface gravity is notoriously difficult to measure for non-degenerate stars, since its amplitude is small in comparison with the typical Doppler shift induced by stellar radial velocity. In this study, we make use of the large observational data set of the Gaia mission to achieve a significant reduction of noise caused by these random stellar motions. By measuring the differences in velocities between the components of the pairs of comoving stars and wide binaries, we are able to statistically measure the combined effects of gravitational redshift and convective blueshifting of spectral lines, and nullify the effect of the peculiar motions of the stars. For the subset of stars considered in this study, we find a positive correlation between the observed differences in Gaia radial velocities and the differences in surface gravity and convective blueshift inferred from effective temperature and luminosity measurements. The results rule out a null signal at the 5σ level for our full data set. Additionally, we study the subdominant effects of binary motion, and possible systematic errors in radial velocity measurements within Gaia. Results from the technique presented in this study are expected to improve significantly with data from the next Gaia data release. Such improvements could be used to constrain the mass–luminosity relation and stellar models that predict the magnitude of convective blueshift.

A novel method for measuring the length of hot large forgings based on machine vision system

In order to measure the length of hot large forgings, a novel method based on machine vision system is proposed. Firstly, according to the characteristics that the light strips in the images acquired by machine vision system are continuous and have peaks, the light strip is detected. Secondly, after calculating the sub-pixel edge points of each light strip using an improved sub-pixel edge detection algorithm, the sub-pixel edge points of each light strip are sorted according to the order of the abscissa from small to large. Three-dimensional (3D) points of each edge can be obtained separately by matching and 3D reconstruction. Finally, the 3D points of each edge are projected onto its fitting plane, and the projected points are fitted with a quintic polynomial curve. According to the curvature of the fitted curve, the edge point of the forging can be detected. The distance from the starting point to the edge point is the length of forging at the position of light strip edge. The length measurement experiment shows that the method can be used to measure the length of hot large forgings. The relative error of the length measurement system is 0.547%. The time for measuring the length of hot forging is 6.8 s.

Haemodynamic changes during radical nephrectomy with inferior vena cava thrombectomy: A pilot study.

Haemodynamic changes during radical nephrectomy with inferior vena cava thrombectomy: A pilot study.

Kalman Filter Based High Precision Temperature Data Processing Method

Obtaining high precision temperature data is crucial in spaceflight applications, considering the growing demand for high precision temperature measurement and the limited onboard resources with a harsh thermal environment in the spacecraft. How to obtain the data, however, becomes an urgent problem. Kalman filtering method is one of the solutions to obtain high precision temperature data with such limited resources. In this paper, the authors demonstrate the principle of temperature measurement system, the application of Kalman filter in temperature measurement including the processing method of sensor self-heating effect, and establishes the state space of measurement error and system error. Through the test, it could be seen that Kalman filtering can improve the temperature measurement resolution to the order of 100 μK while effectively reducing the temperature measurement bias.

The error of transferring the size of a unit of length – a meter in the nanometer range using the nanomeasuring machine

The paper describes the principle of measuring linear dimensions using a nano-measuring machine (NMM), which implements the method of measuring three coordinate axes in the range of 25X25X5 mm3. Sources of non-excluded systematic measurement errors are identified, which are conventionally divided into factors associated with the method of measuring length using an interferometer and factors determined by the design and technological features of the nano-measuring machine. Statistical estimates of the measurement result have been determined and the error in transferring the size – meter length in the nanometer range of measurements has been calculated. The results obtained assert that the nano-measuring machine is a unique tool that allows one to carry out measurements of millimeter dimensions with nanometer accuracy. The results obtained can be used for metrological assessment of the step height and step width, when calibrating measuring instruments in the nanometer range, roughness measures in a large range when calibrating profilometers and contourographs, as well as templates and micrometer objects for measuring high-precision microscopes.