Calibration Solutions Research Articles

Abordagens com redes neurais artificiais para a calibração do coeficiente Kw em redes de distribuição de água

ABSTRACT This study investigates the calibration of the chlorine wall decay coefficient (Kw) in pipelines, a crucial parameter for ensuring the accuracy of water quality models in distribution networks. The developed methodology applies two methods based on artificial neural networks (ANNs): one that calibrates Kw for groups of similar pipelines (group-based ANN (G-ANN)) and another that performs individual calibration for each segment (segment-based ANN). These methods were tested and validated in different scenarios, varying both in the amount of observed data and in the parameter variation range used for generating the training and testing data. The results indicated that G-ANN presented lower error in scenarios with limited observed data, emerging as an efficient solution for calibration in contexts with low data availability. In contrast, the segment-based calibration approach showed greater potential in scenarios where the modeler has a wide range of information about the pipelines and chlorine concentrations at network nodes. In conclusion, this study provides a significant contribution to the improvement of Kw calibration techniques, offering more accurate tools for modeling water distribution networks.

Application of the QuEChERS method combined with UHPLC-QqQ-MS/MS for the determination of isoprocarb and carbaryl pesticides in Indonesian coffee.

The performance of the QuEChERS method in this study, as indicated by a high percentage (>90%) of recovery observations falling within the range of 60-140% and a sample replicate deviation (% RSD) of <20%, for the routine analysis of isoprocarb and carbaryl pesticides, has been evaluated over a 14-month period for the export of Indonesian coffee. Following a seven-day observation of the stability of these pesticides in coffee extract, it was found that the added standard calibration solution remained stable and useable for seven days when stored at 4 °C and -20 °C. This validated method, with high sensitivity (a LOQ of 0.001 mg kg-1 for isoprocarb and carbaryl), has been employed to monitor residues in Indonesian coffee exports to comply with maximum residue limits (MRLs). The samples with higher contamination levels were predominantly from robusta coffee (57.76%), followed by arabica coffee (6.17%). The detection rates for residues decreased by more than 90% in the last two months of the method's application. In the observation of coffee processing, it was found that isoprocarb residues in contaminated samples could be transferred to the processed coffee (roasted and its infusion) to a limited extent, while residues from the carcinogenic carbaryl were not detected due to evaporation. Additionally, chronic dietary risk assessment showed that contaminated samples of robusta and arabica coffees should not be considered a significant public health concern (hazard index HI < 1). However, continuous monitoring of pesticide residues in Indonesian coffee is still recommended, not only to conform to the MRLs of importing countries but also to ensure food trade.

GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices

Due to global air pollution, there is a growing demand for accurate and large-scale air quality monitoring systems. Consequently, low-cost air monitoring devices have emerged as a potential alternative to expensive conventional ones. However, the low-cost devices’ major drawback is their insufficient level of accuracy. This work investigates the problem of calibrating the sensory data, especially PM2.5 concentration, collected by low-cost sensor-based air quality monitoring devices. Recently, deep learning has emerged as a potential solution for data calibration instead of using traditional methods, whose accuracy is relatively low. Nevertheless, it generally incurs significant costs. Moreover, it is necessary to employ a dedicated calibration model for each device to increase precision, resulting in additional expenditures. To address the issue, this study provides a novel approach named GAMMA, which entails the development of a deep learning-based model capable of accurately calibrating data for multiple devices simultaneously. The proposed method leverages the multitask learning paradigm to solve the challenge of concurrently processing several devices’ data. This involves capturing common features across all devices’ data while also distinguishing the device-specific characteristics. Furthermore, GAMMA also employs the adversarial training approach to augment the accuracy of predictions. This method has been implemented and integrated into an air quality monitoring system in Hanoi, Vietnam. Comprehensive experiments are conducted on real-world data to demonstrate the superiority of GAMMA against the comparison benchmarks in terms of various metrics. Notably, GAMMA reduces MAE from 60.19% to 74.09% compared to the best comparison baseline. The source code is available at https://github.com/anhduy0911/FimiCalibIdea/tree/multi_attention.

A two-step solution for robot-world calibration made intelligible by implementing Chasles’ motion decomposition in Ad(SE(3))

As a typical kinematic problem, an important criterion for the accuracy of robot-world calibration is whether the rotational and translational parts are calculated separately or not. Solving the kinematic equation separately increases the interest into the decomposition mode of the equation. This paper provides a decomposition mode for Ad(SE(3)) with embedded Chasles’ motion, providing a new decomposition mode for the robot-world equation. Firstly, the Lie algebra ad(se(3)) for Chasles’ rotational and translational motions are constructed and mapped exponentially to the Lie group Ad(SE(3)) separately, thus implementing the Chasles’ motion decomposition of Ad(SE(3)). Subsequently, the robot-world equation in Ad(SE(3)) is derived based on joint kinematics. A new decomposition mode for robot-world equation is proposed through the Chasles’ motion decomposition, and a two-step method based on point set matching is proposed. Finally, the effect of coordinate invariants on the calibration accuracy is discussed, and the superiority of the proposed method is verified with simulation and experimental tests.

Low-Overhead RF Impedance Measurement Using Periodic Structures

Due to the need for higher reliability and performance from RF circuits, multi-port reflectometers are increasingly used as low-overhead impedance monitors. In this work, using periodic structures as multi-ports is proposed. Periodic structures impose a new constraint on the multi-port theory and simplify it significantly. This simplification leads to closed form solution for calibration and measurement procedures. The closed-form solution also shows that any arbitrary periodic structure will always have a unique solution for both procedures. Therefore, the proposed technique does not rely on frequency-dependent behavior of devices, such as directivity and phase shift to measure impedance. This fact leads to increased bandwidth and simplified design procedure. In addition, proposed multi-port structures can be calibrated by using fewer known loads than existing multi-port techniques. This fact, coupled with the closed-form solution, reduces computation overhead and test time. The theory and its robustness against non-idealities, such as part-to-part variation, are verified with Monte-Carlo simulations. A practical embodiment of the technique is demonstrated with EM simulations and hardware experiments. In this embodiment, the multi-port structure is embedded into an LC matching network. Hardware experiments show that the embedded multi-port structure can measure test loads with high accuracy from 1.5 GHz to 3.5 GHz, without degrading matching network performance.

A-080 Overcoming Challenges of Equilibrium Dialysis-Based Free Thyroxine Measurements

Abstract Background Thyroid function tests are widely used to detect diseases of the thyroid. Concerns about the accuracy and reliability of free thyroxine (FT4) measurements have been stated by the clinical laboratory community. To address these concerns, CDC established a reference measurement procedure (RMP) for FT4 based on equilibrium dialysis (ED). ED-based methods have advantages over traditional direct immunoassays. As with all analytical methods, factors affecting accuracy and reliability of ED-based methods need identification and understanding. To investigate potential sources of error, the CDC FT4 RMP was used to evaluate T4 stability at different of storage conditions, adsorption of FT4 to common labware surfaces, and the effect of dialysis membrane materials on the measured FT4 in serum. Methods FT4 was measured in serum using the IFCC RMP (1). FT4 was separated from the protein-bound form during the equilibrium dialysis step of the RMP. Dialysates were spiked with internal standard (13C6-T4) and the analyte was further isolated by C18 solid phase extraction (SPE) and liquid-liquid extraction (LLE) in ethyl acetate prior to injection on an UHPLC system coupled with a triple quadrupole mass spectrometer. Bracketed calibration and primary reference materials were used to determine FT4 concentration in serum. This procedure was used to evaluate stability of serum FT4 during storage at −70 to 5 °C. Short- and long-term T4 stability of calibrator solutions at −70 °C to ambient temperature and the extent of adsorption of T4 calibrator solutions to the commonly used labware surfaces were evaluated. Furthermore, the suitability of 4 different dialysis membranes was assessed. In addition, three alternatives to the currently used SPE and LLE extraction steps were tested: LLE using cyclohexane and ethyl acetate, LLE with ethyl acetate, and supported liquid extraction with cyclohexane and ethyl acetate. Results T4 calibrator solution was stable in 1.7% ammonium hydroxide in ethanol for at least 2.9 years at −70 °C and up to 7 days at ambient temperature. Exposure of various calibrator solutions such as T4 in ethanol, ethanol with 1.7% ammonium hydroxide, 10% acetonitrile with 0.1% formic acid to common labware resulted in up to 10.1% loss of the analyte. FT4 in serum and T4 in dialysates and extracts were stable at −70 to 5 °C. Use of alternative dialysis membranes resulted in up to −8.8% mean bias to the reference membranes. Recoveries of the analyte using four extraction methods were 85.4%–95.0%. None of the tested extraction conditions significantly changed the results obtained with the original FT4 RMPs. Conclusion Although FT4 RMP must strictly adhere to the ED conditions described for the RMP, other parts of the sample preparation procedures can deviate from the originally published procedure. Careful selection of procedure for calibrator solvents, dialysis membranes, labware, and storage conditions is required to ensure accurate and reproducible FT4 measurements.

Enhancing heliostat calibration on low data by fusing robotic rigid body kinematics with neural networks

Solar tower power plants rely on very precise alignments of their heliostats for efficient operation. To achieve this, the heliostats have to be calibrated regularly. Open-loop calibration procedures are the most common type due to their cost-effectiveness. Two main approaches to these algorithms exist: geometry-based robotic kinematics and neural network-based models. While the former is reliable and requires little data, it only yields moderate accuracy. The latter, however, promises higher accuracies but is data-hungry and unreliable. We here present a two-layer hybrid model that combines a well-established geometric model for pre-alignment with a neural network disturbance model whose impact is gradually adapted through a regularization sweep. This approach ensures that the prediction accuracy is, in the worst-case, equivalent to that of the rigid-body model. Moreover, it helps to identify deficiencies that may have been overlooked by the physical approach. Especially, it is capable to compute deviation from the geometry models averaged optimum. For testing, real measurement data from daily heliostat calibration at the solar tower in Jülich is used. To report accuracies which hold true throughout the year a special training/validation data sampling is employed, which allows for a conservative performance assumption. The results demonstrate that the Hybrid-model outperforms rigid-body models starting from the first measurement, achieving a top performance below 0.7 milliradians. In conclusion, the proposed hybrid model provides a cost effective in-situ solution for heliostat calibration with highest accuracies on low data in solar tower power plants for all open-loop calibration methods.

Occurrence and risk assessment of pesticides and pharmaceuticals in viticulture impacted watersheds from Northwest Spain

An automated analytical methodology was developed, validated and applied to monitor 73 organic pollutants (pesticides and pharmaceuticals) in surface and groundwater samples obtained in watersheds from an intensive viticulture, rural region, in the Northwest of Spain. Filtered samples were concentrated using a reusable solid-phase extraction sorbent, on-line combined with liquid chromatography tandem mass spectrometry (LC-MS/MS). The analytical procedure achieved limits of quantification between 1 ng L−1 and 10 ng L−1, with a throughput of 2 samples hour−1, providing accurate recoveries for more than 90% of the 73 selected compounds, using calibration solutions prepared in ultrapure water (in presence of methanol and formic acid) as neat solvent. The distribution and the concentrations of pesticides in small streams impacted by discharges of treated municipal wastewaters were different in rural and residential areas. On the other hand, pharmaceuticals showed a similar distribution in both streams. In surface waters from viticulture impacted watersheds, with a limited influence of municipal wastewaters, pulses of pesticides were noticed, with values above 100 ng L−1 for several fungicides. Cardiovascular pharmaceuticals, psychiatric drugs and/or their transformation products were also ubiquitous in these samples, with low, but relatively stable concentrations among sampling campaigns. Within the suite of investigated compounds, maximum pesticide residues remained below their predicted-non effect concentration (PNEC) in all samples. On the other hand, the environmental concentrations of the cardiovascular drug olmesartan stayed systematically above its PNEC in fresh water samples.

High-precision simultaneous measurement of 187Os, 186Os, and 184Os using 1013 Ω amplifiers and CDDs on NTIMS

High-precision measurements of 184Os/188Os, 186Os/188Os, and 187Os/188Os ratios are significant in the fields of geochemistry and cosmochemistry. However, no high-precision measurement technique exists for simultaneously obtaining all three ratios using a static method for samples with an Os content of <1 ng or 186OsO3‾ and 187OsO3‾ ion-beam intensities of <150 mV. This greatly limits research on rare samples with small sample sizes or low Os contents, such as Lunar, Martian, or old Earth samples. This paper reports a static method, which could achieve the simultaneous measurement of 9 Faraday cups (FCs) with high-signal/noise ratio 1012 Ω amplifiers and 1013 Ω amplifiers and two compact discrete dynodes (CDDs). By analyzing two calibration solutions, a precision value of less than 3‰ (2RSD) could be achieved for 184Os/188Os ratios, even if the 184OsO3‾ intensity was as low as 1000 cps. The precision values for the 186Os/188Os and 187Os/188Os ratios were similar and could be better than 0.066‰ (2RSD) when the intensities of 186OsO3‾ and 187OsO3‾ were greater than 30 mV, which can be obtained with conventional 1011 Ω amplifiers only at signals larger than 150 mV. Three geological reference materials were used in this study. The precision values of 184Os/188Os, 186Os/188Os, and 187Os/188Os ratios reached 2, 0.061, and 0.050‰ (2RSD), respectively, when the maximum Os amount was approximately 12 ng, and 87, 15, and 10‰ (2RSD), respectively, when the maximum Os amount was as low as approximately 66 pg. Additionally, our results show that changes in the volume of oxygen added during measurement can cause significant variations in the oxygen isotope composition. This static measurement method not only avoids the nonlinear signal change of the instrument during the analysis process but also realizes the accurate removal of the oxygen isobaric interference in the run, which could improve the precision of 184Os/188Os, 186Os/188Os, and 187Os/188Os ratios for small-size/low-signal samples.

Fast Calibration Method for Base Coordinates of the Dual-Robot Based on Three-Point Measurement Calibration Method

Multi-robot systems can perform more complex tasks with high precision and large loads than single-robot systems. The calibration of the base coordinate system is the basis and premise to ensure the collaborative operation between the dual-robot. In this study, a dual-robot calibration system based on calibration tooling components was established, which could quickly and accurately obtain the relative position between dual robots. Based on three reference measurement points of the orthogonal distribution in the calibration tool coordinate system, a mapping relationship between the distance from the reference measurement point to the robot end point and the parameters of the robot base system was established, and a fast dual-robot base system parameter calibration solution method based on "three-point measurement calibration" was proposed. The experimental results show that this method can quickly and accurately obtain the transformation relationship between the dual robot base coordinate systems. The accuracy and efficiency of the calibration have been greatly improved. It is of great significance for meeting the requirements of high efficiency, low cost, and easy operation in the factory application process.

The Radio Parallax of the Crab Pulsar: A First VLBI Measurement Calibrated with Giant Pulses

We use four observations with the European very long baseline interferometry (VLBI) network to measure the first precise radio parallax of the Crab Pulsar. We found two in-beam extragalactic sources just outside the Crab Nebula, with one bright enough to use as a background reference source in our data. We use the Crab Pulsar’s giant pulses to determine fringe and bandpass calibration solutions, which greatly improved the sensitivity and reliability of our images and allowed us to determine precise positional offsets between the pulsar and the background source. From those offsets, we determine a parallax of π = 0.53 ± 0.06 mas and proper motion of (μ α , μ δ ) = (−11.34 ± 0.06, 2.65 ± 0.14) mas yr−1, yielding a distance of and transverse velocity of . These results are consistent with the Gaia 3 measurements, and open up the possibility of far more accurate astrometry with further VLBI observations.

Variable microfluidic dosing valve for gas chromatography

Miniaturization coupled with the introduction of microfluidic systems and devices into the chromatograph hardware is one of the main approaches to the creation of modern gas chromatographic equipment. For variable sample dosing in automatic mode, a microfluidic dosing valve based on microelectromechanical systems was developed. The manufactured device provides multi-point calibration with a single calibration gas mixture. Two methods for constructing a calibration dependence were implemented using the developed dosing device: a calibrated loop for 250 μl taken as a constant dosing loop and calibration solutions (gas mixtures of propane in helium (GSO 10463–2014) with concentrations of 0.0025, 0.025, 0.25, 0.5б and 1.25 % vol.) were used in the first method, whereas in the second one a variable dosing provided by the developed microfluidic dosing valve which consisted in the possibility of introducing a different amount of the calibration gas mixture of propane in helium (2.5 % vol.) into the chromatographic column due to changing the time of sample injection at a constant pressure was implemented. The experiment was carried out on a PIA gas microchromatograph with a MEMS column (a sectional plane of 1 × 1 mm and a 1-m channel) with a Carbopak B adsorbent. It is shown that the use of the developed dosing device as part of the PIA gas microchromatograph makes it possible to carry out a metrologically assured quantitative analysis.

Trajectory-based RFI subtraction and calibration for radio interferometry

ABSTRACT Radio interferometry calibration and radio frequency interference (RFI) removal are usually done separately. Here we show that jointly modelling the antenna gains and RFI has significant benefits when the RFI follows precise trajectories, such as for satellites. One surprising benefit is improved calibration solutions, by leveraging the RFI signal itself. We present trajectory-based RFI subtraction and calibration (tabascal), a new algorithm that jointly models the RFI and calibration parameters in visibilities. We test tabascal on simulated MeerKAT calibration observations contaminated by satellite-based RFI. We obtain gain estimates that are both unbiased and up to an order of magnitude better constrained compared to uncontaminated data. When combined with an ad hoc RFI subtraction scheme, tabascal solutions can be further applied to an adjacent target observation: 5 min of calibration data results in an image with about a third the noise achieved when using flagging alone. The recovered flux distribution of RFI subtracted data was on par with uncontaminated data. In contrast, RFI flagging alone resulted in a higher detection threshold and consistent underestimation of source fluxes. For a mean RFI amplitude of 17 Jy, using RFI subtraction leads to less than 1 per cent loss of data compared to 75 per cent data loss from an ideal 3σ flagging algorithm, a very significant increase in data available for science analysis. Although we have examined the case of satellite RFI, tabascal should work for any RFI moving on parametrizable trajectories, relative to the phase centre, such as planes and/or objects fixed to the ground.

Constitutive modeling of temperature and strain rate effects on anisotropy and strength differential properties of metallic materials

The thermal effects on tension compression asymmetry and anisotropy of several metallic materials with a hexagonal close-packed (HCP) crystal structure have been discussed in this study. The Yoon2014 asymmetric yield criterion is combined with a simple Arrhenius type temperature function and a modified Johnson-Cook strain rate model to formulate a thermal dependent plasticity model with analytical solutions for parameter calibration. The temperature and strain rate effects on the strength differential (SD) effects of both isotropic and anisotropic materials have been discussed. Both anisotropy and SD affect the shape of yield locus. In order to quantitatively distinguish the thermal effects on the strength differential and anisotropic effects of metallic materials, the evolution of yield locus and distribution of yield stress under two extreme scenarios has been discussed based on virtual experimental results. For the general application of the thermal dependent asymmetric plasticity model at different temperatures and strain rates, the calibration and validation of the model using uniaxial tensile/compressive results along different directions and biaxial tensile/compressive results have been elaborated for various metallic alloys.

Offline GNSS/Camera Extrinsic Calibration Using RTK and Fiducials

Accurate robotic state estimation often requires precise knowledge of inter-sensor offsets. In this paper we present a solution for inter-sensor calibration of systems that employ a combination of GNSS and visual-inertial sensors. RTK-GNSS and fiducial measurements are utilized to produce highly precise estimates. We present an offline batch estimation approach that utilizes a continuous-time spline on the Lie group SE(3). This approach simultaneously estimates the vehicle trajectory and sensor spatio-temporal offsets by choosing optimal spline control points and calibration parameters to solve a maximum likelihood estimation problem. Our calibration method is validated in both simulation and hardware, with comparison to an online extended Kalman filter. Hardware experiments are conducted in both a motion capture environment and outdoors. Results show that our method outperforms online methods and approaches millimeter-level accuracy.

EFFECTS OF HYPER HEMISPHERICAL FIELD IN BUNDLE ADJUSTMENT WITH FISHEYE IMAGES

Abstract. The large field of view and compact structure make fisheye lens cameras an attractive technology for mobile mapping systems and visual navigation. Fisheye cameras usually have a field of view equal to or higher than 180°. Lenses that can capture light rays coming from angles larger than 180° are known as hyper hemispherical lenses. Some of the existing mathematical models can be unsuitable for those points beyond the 180° field of view when performing photogrammetric processes based on these equations, underexploring the full potential of fisheye lens cameras. In this case, depending on the selected projection model, points appearing in the hyper hemispherical (HH) field can produce blunders in the bundle adjustment. Nevertheless, most of the available solutions for camera calibration and bundle adjustment were implemented using the equidistant model. Therefore, the points located in the hyper hemispherical field are often removed from the bundle adjustment either during keypoint detection or by applying a mask to remove the entire HH field from the images. In this paper, we assessed experimentally the hypothesis that using the original HH full-field image introduces blunders, deteriorating the bundle adjustment. The experiments were performed with a Ricoh Theta S 360° camera which was mounted on a backpack platform. The camera was set in video mode, and frames were captured at a rate of 1 fps, while traversing an urban street, generating 307 frames. Experiments were performed, including or removing HH points in the bundle adjustment. The results show that the errors in the dataset with the hyper hemispherical field were larger than the ones using cropped images.

Implementation of an Accurate Measurement Method for the Spatial Distribution of the Electromagnetic Field in a WPT System

In an inductive wireless power transfer (WPT) system, the transferred power depends on the coupling between the transmitter coil and the receiver coil and, consequently, on their spatial positioning with respect to each other. Since this positioning needs to be as flexible as possible, one can design various construction shapes for the coils, in terms of both winding geometry and core geometry. The system efficiency for different positionings and configurations can be assessed if the structure and distribution of the electromagnetic field (EMF) in the space close to the system are determined. In this context, this paper proposes an investigation method based on measuring the intensity of the electromagnetic field generated by the emitting coil in the WPT space in terms of both modulus and direction. The measurements needed to be performed at a sufficient number of points, so that the entire field was determined. The EMF value was estimated by linear spatial interpolation between the measured points. Moreover, this paper presents the method and the results of investigations carried out only in the presence of the emitting coil. Calibration or correction solutions were also proposed to obtain sufficient accuracy, and the viability of the method was therefore demonstrated.

Purity Assessment of Dinotefuran Using Mass Balance and Quantitative Nuclear Magnetic Resonance.

Dinotefuran (DNT) belongs to the third-generation neonicotinoid pesticides, which are among the most common residuals in a variety of food commodities. To guarantee accurate quantification and traceability of results in food samples, certified reference materials (CRMs) are the indispensable benchmark. In this work, a DNT CRM was characterized and its purity was assessed by two independent methods, including mass balance (MB) and quantitative nuclear magnetic resonance spectroscopy (qNMR). The mass fraction of moisture was 0.33 mg/g, the inorganic impurity was 0.01 mg/g, and no detectable organic solvent was detected. Benzoic acid was chosen as the internal standard for qNMR. Its mass fraction was 997.9 mg/g and 992.9 mg/g by MB and qNMR, respectively. Eventually, the DNT CRM was assigned a mass fraction of 995 mg/g, with expanded uncertainty of 5 mg/g (k = 2). This CRM can be used to prepare calibrant solutions and is applicable to national routine monitoring of DNT residuals in agro-products and food.

An open‐source tool for evaluating calibration techniques used in low‐cost air pollutant monitors

AbstractLow‐cost air pollutant sensors suffer several interferences due to the variation of climatic elements. Recent studies look for calibration solutions based on different regression and classification machine learning algorithms. The present work brings together the implementation and extraction of performance metrics from these algorithms in a single open‐source tool. Both the input data and parameters for each algorithm are automatically configured. This feature makes the tool compatible with any input dataset and removes the need to interact with complex codes.

Noise measurement and system calibration on magnetoresistive sensors

PurposeThe noise measurement on magnetoresistive (MR) sensors is generally conducted by techniques including single-channel data sampling and fast Fourier transform (FFT) analysis as well as two-channel cross-correlation. The single-channel method is easy to implement and is widely used in the noise measurement on MR sensors, whereas the two-channel method can only eliminate part of the system noise. This study aims to address two key issues affecting measurement accuracy: calibration of the measurement system and the elimination of system noise.Design/methodology/approachThe system is calibrated by using a low-noise metal film resistor in that the system noise is eliminated through power spectrum subtraction. Noise measurement and analysis are conducted for both thermal noise and detectivity of magnetic tunnel junction (MTJ) sensor.FindingsThe thermal noise measurement error is less than 2%. The detectivity of the MTJ sensor reaches 27 pT/Hz1/2 at 2 kHz.Originality/valueThis study provides a more practical solution for noise measurement and system calibration on MR sensors with a bias voltage and magnetic field.