Main Sources Of Measurement Error Research Articles

Methods to mitigate the impact of work environment on the measurement of building surface temperature by unmanned aerial vehicle onboard thermal imaging system

With the widespread adoption of UAVs and compact infrared cameras, UAV infrared remote sensing technology has extensive applications in qualitative research fields such as finding thermal bridges and air tightness detection in construction projects, but less in quantitative research, mainly due to its large temperature measurement error. When measuring temperature with UAV-mounted thermal imaging cameras, factors such as operational wind conditions and operation methods, in addition to the inherent accuracy of the instrument, can introduce measurement errors. To investigate the impact of operational wind conditions on temperature measurements by UAV-mounted thermal imaging cameras, both field and laboratory experiments were conducted to analyze the error characteristics caused by wind conditions. Devices were designed to mitigate the impact of wind on temperature measurements, and their effectiveness was validated through experiments. Based on these findings, methods were developed for reducing the influence of wind conditions on temperature measurements in UAV operations. The results indicate that wind condition errors primarily affect the stability of temperature data. Under the influence of wind conditions, the temperature data recorded by thermal infrared cameras exhibit periodic and significant fluctuations, with a temperature difference of approximately 4.7 °C between the highest and lowest points within a single cycle, constituting the main source of measurement error. However, by following the prescribed measurement procedures, the temperature measurement error can be reduced by 32 %, from ±5 °C to ±1.6 °C, approaching the accuracy of tripod-mounted thermal imaging cameras. This establishes a foundation for quantitative research in low-altitude infrared remote sensing.

Precise Point Positioning on the Reliable Detection of Tropospheric Model Errors.

Precise point positioning (PPP) is one of the well-known applications of Global Navigation Satellite System (GNSS) and provides precise positioning solutions using accurate satellite orbit and clock products. The tropospheric delay due to the neutral atmosphere for microwave signals is one of the main sources of measurement error in PPP. As one component of this delay, the hydrostatic delay is usually compensated by using an empirical correction model. However, how to eliminate the effects of the wet delay during a weather event is a challenge because current troposphere models are not capable of considering the complex atmosphere around the receiver during situations such as typhoons, storms, heavy rainfall, et cetera. Thus, how positioning results can be improved if the residual wet delays are taken into account needs to be investigated . In this contribution, a real-time procedure of recursive detection, identification and adaptation (DIA) is applied to detect the model errors which have the same effects on both phase and code observables; e.g., the model error caused by the tropospheric delay. Once the model errors are identified, additional parameters are added to the functional model to account for the measurement residuals. This approach is evaluated with Global Positioning System (GPS) data during two rainfall events in Darwin, Australia, proving the usefulness of compensated residual slant wet delay for positioning results. Comparisons with the standard approach show that the precision of the up component is improved significantly during the periods of the weather events; for the two case studies, and improvements of root mean squared error (RMS) resulted, and the precision of the horizontal component obtained by the proposed approach is also improved more than compared to the standard approach. The results also show that the identified model errors are concentrated at the beginning of both heavy rainfall processes when the front causes significant spatial and temporal gradients of the integrated water vapor above the receiver.

Importance of over-reading ambulatory ECG-based microvolt T-wave alternans to eliminate three main sources of measurement error.

Ambulatory electrocardiogram (ECG)-based microvolt T-wave alternans values measured by the modified moving average method (MMA-TWA) can be disrupted by T-wave changes that mimic true repolarization alternans. We investigated potential sources of measurement error by studying 19 healthy subjects (12 men; median age, 25) free of known heart disease with 36-month follow-up to establish freedom from significant arrhythmia or syncope. All participants underwent 24-hr continuous 12-lead ECG monitoring. Causes of automated MMA-TWA ≥42µV episodes were classified based on visual inspection. A total of 2,189 episodes of automated MMA-TWA episodes ≥42µV were observed in all subjects (peak MMA-TWA: median, 94μV; interquartile range, 81-112μV). All episodes included one or more beats with T-wave deformation which lacked "repeating ABAB pattern" and therefore were identified as TWA measurement error. Causes of such error were categorized as: (a) artifact [72.6% (1,589/2,189), observed in 19 (100%) subjects], more frequently in limb than precordial leads; (b) T-wave changes due to changes in heart/body position [25.5% (559/2,189), observed in 14 (73.7%) subjects], frequently observed in leads V1-2; and (c) postextrasystolic T-wave changes [1.9% (41/2,189), observed in 2 (10.5%) subjects]. Relying only on automated MMA-TWA values obtained during ambulatory ECG monitoring can lead to incorrect measurement of TWA. Our findings offer the potential to reduce false-positive TWA results and to achieve more accurate detection of true repolarization alternans.

A psychometric evaluation of the job crafting questionnaire (JCRQ) among employees working in Jordanian universities

Purpose Job crafting is recently argued to have five dimensions (Nielsen et al., 2017): increasing challenging demands, decreasing social demands, increasing social job resources, increasing quantitative demands and decreasing hindrance demands. The purpose of this study aimed to investigate the psychometric properties and construct validity of the five-factor model of job crafting, introduced by using a sample of Jordanian university employees. Design/methodology/approach A pre-determined survey on was used. Accordingly, 513 professional workers in several universities completed the survey. Cronbach’s alpha was used to assess the internal consistency of the scale, whereas series of confirmatory factor (CFA) analysis and exploratory factor analysis (EFA) were conducted to assess the scale’s factorial and discriminant validity. Other tests were also conducted. Findings As predicted, the proposed model best fit the data. Statistical analysis yielded several findings. First, the results of the reliability test revealed that the five sub-scales of job crafting had significant and sufficiently strong internal consistencies. Second, the results showed that the 15 items loaded significantly with a factor loadings more than 0.50. Third, the CFA results confirmed that the five-factor model best fitted the data in comparison to the one-factor model. Finally, the construct validity of JCRQ-15 was confirmed through its correlation with several validating variables. Research limitations/implications Some limitations need to be addressed. First, the sample came from participants working in specific Jordanian universities which may limit the generalization that could be made from the results to other occupations. Second, due to the cross-sectional design of the present study, the question remains whether the JCRQ-15 are stable overtime. Third, the common methods bias might be a problem because it is one of the main sources of measurement error in validation studies using self-reported scales. Originality/value The present study provided an early supportive evidence for the use of the JCRQ-15 as a valid measure of job crafting in the Jordanian context.

Techniques for communication repair in the standardized telephone interview

It is hardly possible to conduct a standardized interview in ideal conditions for it is a part of everyday interactions. Therefore, deviations from standardization, bias and mistakes in communication are the realities of public opinion polls. Key biases in information transfer are mainly determined by the characteristics of the respondent (age, sex, education, social status, etc.) and his behavior. However, the interviewer behavior is also important which explains the attention of methodological works to the interviewer effect, his actions and attitudes that lead to serious mistakes in measurement or recruiting. In verbal interaction, the interviewer can explain survey questions in his own way, comment or clarify responses. Standardization can also be violated by other circumstances such as interruptions in telephone network, intervention of third parties, technical problems (software malfunction), structure of the questionnaire and so on. Thus, there are three main sources of measurement error in the standardized interview: respondent, interviewer, and context. The qualified and experienced interviewer more successfully identify problems and find ways to solve them and repair communication. The article presents examples of such ways from the database of transcripts of three RDD ACATI surveys conducted by the Laboratory for Social Research Methodology of the Russian Presidential Academy for National Economy and Public Administration in 2017 to identify key types of successful interviewer decisions. They are considered in three dimensions: adequate responses, communication and standardization. Thus, successful interview is not just a completed questionnaire but also relevant answers, informed consent and positive emotional attitude.

Statistical analysis of lung nodule volume measurements with CT in a large-scale phantom study.

To determine inter-related factors that contribute substantially to measurement error of pulmonary nodule measurements with CT by assessing a large-scale dataset of phantom scans and to quantitatively validate the repeatability and reproducibility of a subset containing nodules and CT acquisitions consistent with the Quantitative Imaging Biomarker Alliance (QIBA) metrology recommendations. The dataset has about 40 000 volume measurements of 48 nodules (5-20 mm, four shapes, three radiodensities) estimated by a matched-filter estimator from CT images involving 72 imaging protocols. Technical assessment was performed under a framework suggested by QIBA, which aimed to minimize the inconsistency of terminologies and techniques used in the literature. Accuracy and precision of lung nodule volume measurements were examined by analyzing the linearity, bias, variance, root mean square error (RMSE), repeatability, reproducibility, and significant and substantial factors that contribute to the measurement error. Statistical methodologies including linear regression, analysis of variance, and restricted maximum likelihood were applied to estimate the aforementioned metrics. The analysis was performed on both the whole dataset and a subset meeting the criteria proposed in the QIBA Profile document. Strong linearity was observed for all data. Size, slice thickness × collimation, and randomness in attachment to vessels or chest wall were the main sources of measurement error. Grouping the data by nodule size and slice thickness × collimation, the standard deviation (3.9%-28%), and RMSE (4.4%-68%) tended to increase with smaller nodule size and larger slice thickness. For 5, 8, 10, and 20 mm nodules with reconstruction slice thickness ≤0.8, 3, 3, and 5 mm, respectively, the measurements were almost unbiased (-3.0% to 3.0%). Repeatability coefficients (RCs) were from 6.2% to 40%. Pitch of 0.9, detail kernel, and smaller slice thicknesses yielded better (smaller) RCs than those from pitch of 1.2, medium kernel, and larger slice thicknesses. Exposure showed no impact on RC. The overall reproducibility coefficient (RDC) was 45%, and reduced to about 20%-30% when the slice thickness and collimation were fixed. For nodules and CT imaging complying with the QIBA Profile (QIBA Profile subset), the measurements were highly repeatable and reproducible in spite of variations in nodule characteristics and imaging protocols. The overall measurement error was small and mostly due to the randomness in attachment. The bias, standard deviation, and RMSE grouped by nodule size and slice thickness × collimation in the QIBA Profile subset were within ±3%, 4%, and 5%, respectively. RCs are within 11% and the overall RDC is equal to 11%. The authors have performed a comprehensive technical assessment of lung nodule volumetry with a matched-filter estimator from CT scans of synthetic nodules and identified the main sources of measurement error among various nodule characteristics and imaging parameters. The results confirm that the QIBA Profile set is highly repeatable and reproducible. These phantom study results can serve as a bound on the clinical performance achievable with volumetric CT measurements of pulmonary nodules.

A new global zenith tropospheric delay model IGGtrop for GNSS applications

Tropospheric delay is one of the main sources of measurement error in global navigation satellite systems. It is usually compensated by using an empirical correction model. In this paper, temporal and spatial variations of the global zenith tropospheric delay (ZTD) are further analyzed by ZTD time series from global International GNSS Service stations and annual ZTDs derived from global National Centers for Environmental Prediction reanalysis data, respectively. A new ZTD correction model, named IGGtrop, is developed based on the characteristics of ZTD. Experimental results show that this new 3D-grid-based model that accommodates longitudinal as well as latitudinal variations of ZTD performs better than latitude-only based models (such as UNB3, EGNOS, and UNB3m). The global average bias and RMS for IGGtrop are about −0.8 cm and 4.0 cm, respectively. Bias values for UNB3, EGNOS, and UNB3m are 2.0, 2.0, and 0.7 cm, respectively, and respective RMS values 5.4, 5.4, and 5.0 cm. IGGtrop shows much more consistent prediction errors for different areas than EGNOS and UNB3m. In China, the performance of IGGtrop (bias values from −2.0 to 0.4 cm and RMS from 2.1 to 6.4 cm) is clearly superior to those of EGNOS and UNB3m. It is also demonstrated that IGGtrop biases vary little with height, and its RMS values tend to decrease with increasing height. In addition, IGGtrop generally estimates ZTD with greater accuracy than EGNOS and UNB3m in the Southern Hemisphere.

Measuring the biases in self-reported disability status: evidence from aggregate data

Self-reported health status measures are generally used to analyse Social Security Disability Insurance's (SSDI) application and award decisions as well as the relationship between its generosity and labour force participation. Due to endogeneity and measurement error, the use of self-reported health and disability indicators as explanatory variables in economic models is problematic. We employ county-level aggregate data, instrumental variables and spatial econometric techniques to analyse the determinants of variation in SSDI rates and explicitly account for the endogeneity and measurement error of the self-reported disability measure. Two surprising results are found. First, it is shown that measurement error is the dominating source of the bias and that the main source of measurement error is sampling error. Second, results suggest that there may be synergies for applying for SSDI when the disabled population is larger.

Performance research and optimization on the fan test system based on experiment

To investigate the fan performance of air conditioning system, two different configuration fan test systems are designed. All scale simulation of the two systems provide the basis for design and improvement of air conditioning system fans to improve the internal flow, increase air volume, and reduce the noise. The conclusion that disturbance on flow of nuzzle outlet is the main sources of measurement error about 5% can be proved by the comparative analysis of the results between computation and experiment. Through Optimization Design of Partial Structure they all meet the industry standard, measurement error less than 1.5%.

A method for monitoring reactive strength index

Ubiquitous motion sensors in shoes and clothing are becoming more prevalent. This new data stream opens a large opportunity to gain a deeper understanding of human movement. This paper describes the development and validation of an algorithm to calculate reactive strength index (RSI) from an accelerometer mounted at the ankle. Compared to the gold standard force-plate, the accelerometer and algorithm RSI had r=0.98, mean difference=0.001 m/sec and a confidence interval ranging from 0.12 to −0.11 m/sec. Difficulty in accurately identifying take-off using the accelerometer was the main source of measurement error.

Measurement error and reliability testing: Application to rehabilitation

Aims: Effective measurement of clinical outcomes is dependent on reliable outcome instruments. Measurement error and reliability testing are fundamental underpinnings of reliability. This article defi nes and illustrates sources of measurement error, outlines strategies for error minimization, and gives an overview of the types of reliability studies. Content: The two main sources of measurement error: systematic bias and random error, are discussed. The three major types of reliability evaluation are then illustrated: test-retest; intra-rater and inter-rater reliability, and the relationship between reliability and validity is explained. Discussion and conclusions: Quantifi cation of measurement error is integral to determining the true effect of therapy, as quantifi ed by outcome measurement. Interpretation of reliability data involves consideration of many factors including demographic, diagnostic and clinical characteristics of the study sample.

Precision and accuracy of surface resistance measurement with the dielectric resonator method

The surface resistance of high-T/sub c/ superconducting films at microwave frequencies was measured by the dielectric resonator method using two sapphire rods. The dielectric resonator method is appropriate for the standard measurement of surface resistance at microwave frequencies. We focused on several sources of error in this method, i.e., temperature inhomogeneity in the resonator, asymmetry in coupling and the parasitic coupling effect, and discussed the precision and accuracy of the measurements. It was found that parasitic coupling is the main source of measurement error and we proposed several types of resonators to eliminate the parasitic coupling. These results were reflected in the working draft of the International Electrotechnical Commission Technical Committee 90(IEC/TC90).

Diurnal and seasonal variations of stratomesospheric ozone: Analysis of ground‐based microwave measurements in Bordeaux, France

Atmospheric ozone spectra recorded since September 1985 with a millimeter‐wavelength radiotelescope located at Bordeaux Observatory are used to determine ozone profiles. These concentrations are retrieved using the Backus‐Gilbert inversion method. The experimental difficulties due to the so‐called baseline effect, calibration errors, and fluctuations in the temperature profile are discussed and their influence on the ozone density evaluated. Three heights are optimally selected at 33, 42, and 55 km. The main source of measurement error is the baseline effect. As this affects strongly the ozone density retrieved at 33 km, results are given only for two layers: 42±4.5 km and 55±8 km. Diurnal variations can be estimated in the 42±4.5 km layer during three periods, September 1985, September 1989, and October 1989 with the daytime decrease about 5%–10%. In the 55±8 km layer the variations for these three periods can reach 30%. For both layers the measured variation is greater than that predicted by models because the resolving power of the measurement spreads over higher layers where the variation is actually larger. At 42±4.5 km, seasonal variations in ozone concentration exhibit a semiannual oscillation with summer maxima and pronounced winter peaks. At 55±8 km the daytime and nighttime seasonal variations in ozone concentration exhibit a semiannual oscillation with large summer maxima and small winter peaks.

Effect of surface curvature on measurement of the absorptance properties of solar coatings

A procedure has been developed for determining the spectral hemispherical reflectance properties of solar coatings applied to curved surfaces. The main source of measurement error results from lost reflected radiation which is a function of both the sample size and measurement beam diameter. The magnitude of this error is easily determined through the use of secondary standards. This procedure has also been used in emittance measurements where secondary emittance standards were required.