Propagation Of Systematic Errors Research Articles

BEYONDPLANCK

End-to-end simulations play a key role in the analysis of any high-sensitivity cosmic microwave background (CMB) experiment, providing high-fidelity systematic error propagation capabilities that are unmatched by any other means. In this paper, we address an important issue regarding such simulations, namely, how to define the inputs in terms of sky model and instrument parameters. These may either be taken as a constrained realization derived from the data or as a random realization independent from the data. We refer to these as posterior and prior simulations, respectively. We show that the two options lead to significantly different correlation structures, as prior simulations (contrary to posterior simulations) effectively include cosmic variance, but they exclude realization-specific correlations from non-linear degeneracies. Consequently, they quantify fundamentally different types of uncertainties. We argue that as a result, they also have different and complementary scientific uses, even if this dichotomy is not absolute. In particular, posterior simulations are in general more convenient for parameter estimation studies, while prior simulations are generally more convenient for model testing. Before BEYONDPLANCK, most pipelines used a mix of constrained and random inputs and applied the same hybrid simulations for all applications, even though the statistical justification for this is not always evident. BEYONDPLANCK represents the first end-to-end CMB simulation framework that is able to generate both types of simulations and these new capabilities have brought this topic to the forefront. The BEYONDPLANCK posterior simulations and their uses are described extensively in a suite of companion papers. In this work, we consider one important applications of the corresponding prior simulations, namely, code validation. Specifically, we generated a set of one-year LFI 30 GHz prior simulations with known inputs and we used these to validate the core low-level BEYONDPLANCK algorithms dealing with gain estimation, correlated noise estimation, and mapmaking.

Development and Validation of Machine-Learning Clear-Sky Detection Method Using 1-Min Irradiance Data and Sky Imagers at a Polluted Suburban Site, Xianghe

Clear-sky detection (CSD) is of critical importance in solar energy applications and surface radiative budget studies. Existing CSD methods are not sufficiently validated due to the lack of high-temporal resolution and long-term CSD ground observations, especially at polluted sites. Using five-year high resolution ground-based solar radiation data and visual inspected Total Sky Imager (TSI) measurements at polluted Xianghe, a suburban site, this study validated 17 existing CSD methods and developed a new CSD model based on a machine-learning algorithm (Random Forest: RF). The propagation of systematic errors from input data to the calculated global horizontal irradiance (GHI) is confirmed with Mean Absolute Error (MAE) increased by 99.7% (from 20.00 to 39.93 W·m−2). Through qualitative evaluation, the novel Bright-Sun method outperforms the other traditional CSD methods at Xianghe site, with high accuracy score 0.73 and 0.92 under clear and cloudy conditions, respectively. The RF CSD model developed by one-year irradiance and TSI data shows more robust performance, with clear/cloudy-sky accuracy score of 0.78/0.88. Overall, the Bright-Sun and RF CSD models perform satisfactorily at heavy polluted sites. Further analysis shows the RF CSD model built with only GHI-related parameters can still achieve a mean accuracy score of 0.81, which indicates RF CSD models have the potential in dealing with sites only providing GHI observations.

Factors to be considered in establishing a scanning laboratory for testing the accuracy of terrestrial laser scanning technologies

Laser scanning is a 21st century mapping technique that is used to generate high density point cloud data in three dimensions (3D). The 3D scans can be used for surveying, mapping and monitoring of rock mass movement in mining. For high precision and reliable work, the instrument must be used correctly, regularly calibrated and checked to ensure that it constantly performs according to manufacturer's specifications. In this study, a Leica Total Station TCR 1201+ and a Trimble S6 Total Station were used to establish accurate coordinates for a control beacon and scanning targets. Thereafter, the scanning of the targets was carried out using a FARO Focus XD 130 terrestrial laser scanner. A comparison was conducted using the coordinates from the terrestrial laser scanner and total station to examine the point accuracy of the FARO scanner. The result from the comparison between the laser scanners coordinates and the total station coordinates showed that the FARO Focus is capable of producing accurate point cloud data that can be used for the purpose of monitoring underground rock mass movements. Lessons learnt during the development of the short-range scanning laboratory are summarised as factors to be considered when establishing such a laboratory. These include, operator knowledge, skill and work flow, robust target design, scanning geometry, full target visibility during scanning, calibration of instruments, laser scanner field of view and application of systematic error propagation during measurements.

STUDI PERAMBATAN KESALAHAN SISTEMATIS LUAS LAHAN PARKIR KAMPUS MENGGUNAKAN PENDEKATAN LUAS SEGITIGA SEMBARANG

Parking is a condition of not moving a vehicle that is temporary because it was abandoned by the driver. Included in the definition of parking is every vehicle that stops at certain places whether stated by traffic signs or not, and not solely for the benefit of raising and / or lowering people and / or goods.Campus 3 Lumajang State Community Academy has facilities and infrastructure prepared by the Lumajang Regency government. However, the parking lots provided cannot accommodate vehicles optimally because of the ratio of the number of vehicles and the area of the parking area that is not appropriate. This is because the area of the parking lot is not analyzed by data error when measuring.Each measurement data is assumed to have errors both systematic errors, random errors, and large errors (blunders), so that in the measurement of parking lots certainly there are errors. From this the authors intend to conduct research to find out how the propagation of systematic errors and the large systematic errors of the area of campus parking lot 3 Lumajang Community Academy.The methods used in this study include preparing materials and tools, making land sketches, decomposing them, determining distances using theodolite, determining land area equations, and finding systematic error propagation. So that the final goal in this study is to find large systematic errors in the parking area of Campus 3 of the Lumajang State Community Academy

Plant carbon assimilation rates in atmospheric CO2 reconstructions.

Fossil plant gas-exchange-based CO2 reconstructions use carbon (C) assimilation rates of extant plant species as substitutes for assimilation rates of fossil plants. However, assumptions in model species adoption can lead to systematic error propagation. We used a dataset of c. 2500 extant species to investigate the role of phylogenetic relatedness and ecology in determining C assimilation, an essential variable in gas-exchange-based CO2 models. We evaluated the effect on random and systematic error propagation in atmospheric CO2 caused by adopting different model species. Phylogenetic relatedness, growth form, and solar exposure are important predictors of C assimilation rate. CO2 reconstructions that apply C assimilation rates from modern species based solely on phylogenetic relatedness to fossil species can result in CO2 estimates that are systematically biased by a factor of >2. C assimilation rates used in CO2 reconstructions should be determined by averaging assimilation rates of modern plant species that are (1) in the same family and (2) have a similar habit and habitat as the fossil plant. In addition, systematic bias potential and random error propagation are greatly reduced when CO2 is reconstructed from multiple fossil plant species with different modern relatives at the same site.

Refinement of the ISABELE method regarding uncertainty quantification and thermal dynamics modelling

In the construction sector, strong efforts are being made to reduce energy consumption in buildings, particularly regarding thermal insulation in northern countries. However, the objectives set for the thermal insulation performance of the building envelopes are rarely achieved in practice. For this reason, there is increasing interest in taking onsite measurements. This paper presents the new achievements obtained by the ISABELE (In Situ Assessment of the Building EnveLope pErformances) method for data treatment to evaluate the global transmission heat transfer coefficient of a building with a consolidated uncertainty and within a short unoccupied period. Most of the work relates to the quantification and propagation of systematic errors and to the adaptation of the thermal model used for the inverse method. Practical applications on a test cell and a demonstration on a low-energy house in real outdoor conditions are presented, as are comparisons with other measurement methods (coheating, Quick U-Value of Buildings (QUB)) and the resulting calculated parameters, which show coherent outcomes. The test cell results reveal that a stabilized, repeatable measure with an acceptable uncertainty range ( ± 10 % in average) can be obtained within 2 days. The house results are slightly less precise ( ± 15-20 %) but can be obtained just as quickly, assuming that both configurations are insulated from the inside.

Geometry of GPS relative positioning

GPS positioning is often assimilated to trilateration and even to triangulation methods. Both comparisons are wrong because GPS observations are pseudoranges containing clock errors. The geometric interpretations of GPS relative positioning and trilateration method are presented. Receiver clock parameter is also analyzed from a geometric point of view. The generalization of positioning solutions is made without and with observations redundancy. The geometry of the propagation of systematic errors into positioning solutions is also shown, especially the tropospheric (and the ionospheric) delay.

Propagation of errors associated with scaling foliage biomass from field measurements to remote sensing data over a northern Canadian national park

If a change detection result based on time series of remote sensing data indicates that there was a 10% increase in an ecosystem property between two years over a specific land area, does it mean there was a real change in the ecosystem property, or could it be merely an estimation error? This question must be addressed before ecosystem managers or policy makers can use the result with confidence for addressing related environmental or natural resource management issues. One means of answering this question is through systematic error propagation analysis. In this study, we analyzed error propagation for detecting inter-annual changes in foliage biomass over Wapusk National Park, Canada. Specifically, we first estimated uncertainties in all input data, including sampling errors in foliage and random errors in AVHRR and Landsat data. Secondly, we evaluated the error propagation from inputs to the remote sensing-derived foliage biomass estimates (including the Landsat-based foliage biomass, AVHRR-derived foliage biomass, and the inter-annual changes in foliage biomass), and determined the threshold of detectable change in foliage biomass. Finally, we investigated approaches that can reduce the threshold. Our results indicated that over Wapusk National Park during 1985–2006, the threshold for a clear-sky AVHRR pixel between two single years was ~40% with a confidence level of 84%, and can be reduced to 10% for a land cover class with more than 10 clear-sky AVHRR pixels between two 5-year “State of Park” reporting periods.

Errors in NAPL Volume Estimates Due to Systematic Measurement Errors during Partitioning Tracer Tests

During moment-based analyses of partitioning tracer tests, systematic errors in volume and concentration measurements propagate to yield errors in the saturation and volume estimates for nonaqueous phase liquid (NAPL). Derived expressions could be applied to help practitioners bracket their estimates of NAPL saturation and volume obtained from such tests. In practice, many of these effects may be overshadowed by other complications experienced in the field. Errors are propagated for systematic constant (offset) volume, proportional volume, and constant (offset) concentration errors. Previous efforts to quantify the impact of these errors were predicated upon the specific assumption that nonpartitioning and partitioning masses were equal. The current work relaxes that assumption and is therefore more general in scope. Through the use of nondimensional concentration, systematic proportional concentration errors do not affect the accuracy of the method. Specific consideration needs to be given to accurate flow measurements and minimizing baseline concentration errors when performing partitioning tracer tests in order to prevent the propagation of systematic errors.

Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy

Near-infrared spectroscopy (NIRS) and diffuse optical imaging (DOI) are finding widespread application in the study of human brain activation, motivating further application-specific development of the technology. NIRS and DOI offer the potential to quantify changes in deoxyhemoglobin (HbR) and total hemoglobin (HbT) concentration, thus enabling distinction of oxygen consumption and blood flow changes during brain activation. While the techniques implemented presently provide important results for cognition and the neurosciences through their relative measures of HbR and HbT concentrations, there is much to be done to improve sensitivity, accuracy, and resolution. In this paper, we review the advances currently being made and issues to consider for improving optical image quality. These include the optimal selection of wavelengths to minimize random and systematic error propagation in the calculation of the hemoglobin concentrations, the filtering of systemic physiological signal clutter to improve sensitivity to the hemodynamic response to brain activation, the implementation of overlapping measurements to improve image spatial resolution and uniformity, and the utilization of spatial prior information from structural and functional MRI to reduce DOI partial volume error and improve image quantitative accuracy.

Mathematical Derivative Applied to International Normalised Ratio and Analytical Variations in Oral Anticoagulant Therapy Control

A reliable prothrombin time (PT) testing and a careful drug dosage can prevent thrombotic or bleeding complications of the oral anticoagulant therapy. The international normalised ratio (INR) as PT standardisation introduced an analytical variation that increases with higher PT measures and higher international sensitivity index (ISI) values. Our study was conducted to investigate the INR accuracy through the mathematical derivative application to reduce the analytical component of the INR uncertainty. The evaluation of accuracy among four different systems (prothrombin activity percent, PT seconds, PT ratio and INR) was determined by the simulation of a systematic error. Plasma samples were diluted 1:2; then they were compared observed with the expected values. We analysed the calculation system of the INR through the mathematical derivative in 87 PT ratio measurements. The analytical incidence of thromboplastin ISI was performed through an elaboration of INR mathematical derivative considering 10 different ISI values ranging from 1.1 to 2. The data expressed as PT ratios revealed a lower systematic error propagation suggesting that a linear system is more accurate. According to the calculation formula of INR, analytical variability increases with the PT measurements, then with the intensity of anticoagulation. Mathematical derivative suggests that the INR uncertainty due to the ISI can be reduced using a thromboplastin reagent with a low ISI or with ISI close to 1.

PROPAGATION OF SYSTEMATIC ERRORS IN A ONE LAYER PRIMITIVE-EQUATION MODEL FOR SYNOPTIC SCALE MOTION

Abstract A one-layer, mid-latitude, beta-plane channel model of an incompressible homogeneous fluid is constructed to study the propagation of systematic errors on a nearly stationary synoptic scale wave. A time- and space-centered difference scheme is used to evaluate the governing primitive equations. Data fields resulting from height field perturbations injected at various locations in the synoptic wave are compared to the unperturbed synoptic wave at 3-hr intervals for 5 model days. Results show that the low-frequency or quasi-geostrophic component of the error tends to move toward the core of maximum velocity in the basic state and that, after 5 days, these maximum height errors are in the core regardless of the location of the initial perturbation.