Alternative Calibration Method Research Articles

Technical note: Micro-computed tomography calibration using dental tissue for bone mineral research.

Computed tomography (CT) and microcomputed tomography (μCT) require calibration against density phantoms scanned with specimens or during routine internal calibration for assessment of mineral concentration (MC) and density. In clinical studies involving bone, alternative calibration methods using bodily tissues and fluids ("phantomless" calibration) have been suggested. However, such tissues are seldom available in archeological and osteological research. This study investigates the potential of dental tissue as internal reference for calibration of μCT scans, facilitating the analysis of bone MC. We analyzed 70 molars from 24 extant primate species, including eight human teeth, each scanned with density phantoms for calibration. Our findings indicate that sampling specific regions of molars (lateral aspects of the mesial cusps) yields low variation in enamel and dentine MC values, averaging 1.27 g/cm3 (±0.03) for dentine and 2.25 g/cm3 (±0.03) for enamel. No significant differences were observed across molar types or amongscanning procedures, including scanner model, resolution, and filters. An ad hoc test on 12 mandibles revealed low variance in MC between the conventional phantom and dental tissue calibration methods; all 36 measurements (low, medium, and high MC for each mandible) were within 0.05 g/cm3 of each other -81% were within 0.03 g/cm3 and 94% within 0.04 g/cm3. Based on these results, we propose a new "phantomless" calibration technique using these mean enamel and dentine MC values. The presented phantomless calibration method could aid in the assessment of bone pathology and enhance the scope of studies investigating bone structure and physical property variations in archeological, osteological, and laboratory-based research.

Autocalibration of the E3SM Version 2 Atmosphere Model Using a PCA‐Based Surrogate for Spatial Fields

AbstractGlobal Climate Model tuning (calibration) is a tedious and time‐consuming process, with high‐dimensional input and output fields. Experts typically tune by iteratively running climate simulations with hand‐picked values of tuning parameters. Many, in both the statistical and climate literature, have proposed alternative calibration methods, but most are impractical or difficult to implement. We present a practical, robust, and rigorous calibration approach on the atmosphere‐only model of the Department of Energy's Energy Exascale Earth System Model (E3SM) version 2. Our approach can be summarized into two main parts: (a) the training of a surrogate that predicts E3SM output in a fraction of the time compared to running E3SM, and (b) gradient‐based parameter optimization. To train the surrogate, we generate a set of designed ensemble runs that span our input parameter space and use polynomial chaos expansions on a reduced output space to fit the E3SM output. We use this surrogate in an optimization scheme to identify values of the input parameters for which our model best matches gridded spatial fields of climate observations. To validate our choice of parameters, we run E3SMv2 with the optimal parameter values and compare prediction results to expertly‐tuned simulations across 45 different output fields. This flexible, robust, and automated approach is straightforward to implement, and we demonstrate that the resulting model output matches present day climate observations as well or better than the corresponding output from expert tuned parameter values, while considering high‐dimensional output and operating in a fraction of the time.

An Alternative Calibration Method for Measuring N2O5 with an Iodide-Chemical Ionization Mass Spectrometer and Influencing Factors.

In this work, we developed an alternative calibration method for measuring N2O5 with an iodide adduct mass spectrometer (I-CIMS). In this calibration method, N2O5 is heated and then quantified based on the decrease in the amount of NO due to its reaction with the pyrolysis product (NO3). This alternative calibration method was compared with the commonly used method utilizing NOx analyzers equipped with a photolytic converter, which gauge NO2 reduction as a result of its reaction with O3 to quantify N2O5. It is notable that the two methodologies demonstrate favorable consistency in terms of calibrating N2O5, with a variance of less than 10 %. The alternative calibration method is a more reliable way to quantify N2O5 with CIMS, considering the instability of the NO2 conversion efficiency of photolytic converters in NOx analyzers and the loss of N2O5 in the sampling line. The effects of O3 and relative humidity (RH) on the sensitivity toward N2O5 were further examined. There was minimal perturbation of N2O5 quantification upon exposure to O3 even at high concentrations. The N2O5 sensitivity exhibited a nonlinear dependence on RH as it initially rose and then fell. Besides I(N2O5)-, the collisional interaction between I(H2O)- and N2O5 also forms I(HNO3)-, which may interfere with the accurate quantification of HNO3. As a consequence of the pronounced dependence on humidity, it is advisable to implement humidity correction procedures when conducting measurements of N2O5.

‘Self-calibration’ method for TALIF measurement of O atoms by full photofragmentation of O3 using a 226 nm UV laser

Quantification of atomic oxygen through the method of two-photon absorption laser-induced fluorescence (TALIF) is common in the fields of plasma fundamental research and application treatments. Fluorescence signal calibration is required to absolutely quantify the O amount and normally achieved with the help of TALIF measurement of a known-density Xe gas. In this study, an alternative calibration method is proposed based on the full photofragmentation (FPF) of O3 with a known density in a known gas composition by the same UV laser beam as that of the TALIF detection of atomic O. This is achieved by an equivalent amount of O fragment contributing the same fluorescence intensity as that of the O3 FPF-TALIF process under the same experimental conditions. The validity of this calibration method is proved by comparing it to the TALIF measurement of the Xe gas. It provides a ‘self-calibration’ method for the TALIF detection of O atoms without any need to change the laser optical arrangements including the laser wavelength. In addition, it only requires a gas flow with known O3 density through the studied medium reactor or chamber (such as plasma discharges). Detailed theoretical and practical principles of this self-calibration approach are presented and discussed in this study.

Alternative audiometric calibration methods: Evaluation of sound level measuring apps for audiometric calibration

Audiometric calibration, which includes the calibration of different audiometer transducers and the measurements of ambient noise levels, is historically carried out using Class 1 sound level meters. As technologies advance, many mobile applications (apps) have been developed to measure sound levels. These apps can provide alternative methods for audiometric calibration in places where sound level meters are not available, such as field testing environments, low-to-mid-income countries, and humanitarian settings. These apps, however, cannot be used for audiometric calibration without first evaluating their performance, which depends on multiple factors including the external components (if any), the operating system and the hardware of the electronic devices. The evaluation of the apps is actually the evaluation of the app and associated factors (i.e., the app systems). This paper discusses methods to assess several key functions of apps implemented in either Android or iOS operation system for audiometric calibration: 1) checking the measurement accuracy at all testing frequencies, 2) deriving and using correction factors, 3) determining the self-noise levels, and 4) evaluating the linear/measurement range. As audiometric calibration usually uses octave or 1/3 octave bands to measure sound pressure levels of tones and narrowband noises with relatively steady temporal characteristics, the accuracy of an app can be evaluated by comparing the levels measured by the app and a Class 1 sound level meter at each frequency. The level difference between the app and the Class 1 sound level meter at each frequency can then be used to calculate correction factors that can be added to subsequent levels measured by the app to improve its accuracy. In addition, methods to determine the self-noise level and the linearity range of apps are discussed. Sample measurement scenarios and alternative methods are provided to illustrate the evaluation process to determine whether an app is suitable for measuring ambient noise levels and for calibrating different audiometric transducers.

Dynamic calibration with approximate Bayesian computation for a microsimulation of disease spread

The global COVID-19 pandemic brought considerable public and policy attention to the field of infectious disease modelling. A major hurdle that modellers must overcome, particularly when models are used to develop policy, is quantifying the uncertainty in a model’s predictions. By including the most recent available data in a model, the quality of its predictions can be improved and uncertainties reduced. This paper adapts an existing, large-scale, individual-based COVID-19 model to explore the benefits of updating the model in pseudo-real time. We use Approximate Bayesian Computation (ABC) to dynamically recalibrate the model’s parameter values as new data emerge. ABC offers advantages over alternative calibration methods by providing information about the uncertainty associated with particular parameter values and the resulting COVID-19 predictions through posterior distributions. Analysing such distributions is crucial in fully understanding a model and its outputs. We find that forecasts of future disease infection rates are improved substantially by incorporating up-to-date observations and that the uncertainty in forecasts drops considerably in later simulation windows (as the model is provided with additional data). This is an important outcome because the uncertainty in model predictions is often overlooked when models are used in policy.

Calibration of the Greenhouse Gas Monitoring Instrument (GMI) Based on a Digital Calibration Field Network

The Greenhouse Gas Monitoring Instrument (GMI), carried by Gaofen 5 (GF5-01), and the Hyperspectral Observation Satellite (GF5-02) were successfully launched on 9 May 2018, and September 7, 2021, respectively, and are the only passive greenhouse gas payloads in China that can regularly obtain effective detection data in-orbit at this stage. Before launch, the research team carried out much laboratory calibration work and designed an on-board calibration system based on solar radiation sources which guarantees the quantitative accuracy of the payload data to the greatest extent. In order to more effectively meet the high frequency calibration requirements over the whole life cycle of the payload, the research team carried out research using the on-track site calibration method based on digital calibration field network technology, and the obtained calibration coefficient effectively complements the laboratory and on-board calibration results. The working principle of the GMI is quite different from that of a traditional imaging payload. Spatial heterodyne spectroscopy (SHS) is used to detect the absorption spectrum of greenhouse gases, has a large field of view and is non-imaging and hyperspectral. The existing fixed-site alternative calibration methods cannot fully meet the requirements of calibration tasks. In this paper, we propose a set of global digital calibration radiation field screening criteria that can meet the characteristics of the GMI and design a method to calculate the site calibration coefficients of non-absorption spectral channels according to the characteristics of hyperspectral data. Based on the historical observation data of the GMI, the initial calibration calculation of the payload launch was carried out, and the calibration results of four spectral channels of the GMI were obtained: The calibration coefficient range of the O2 channel is 1.05–1.15, the mean value is 1.10 and the standard deviation is 2.72%; the calibration coefficient of the CO2-1 channel is 1.05–1.13, the mean value is 1.09 and the standard deviation is 2.64%; the calibration coefficient of the CH4 channel is 1.08–1.10, the mean value is 1.11 and the standard deviation is 2.73%; the calibration coefficient of the CO2-2 channel is 1.09–1.14, the mean value is 1.12 and the standard deviation is 2.93%. The above results show that the radiation performance of each channel of the GMI shows no significant attenuation during this period, that the site calibration coefficient has no significant fluctuation and that the in-orbit operation state is stable.

Reliable and Traceable Temperature Measurements Using Thermocouples

Temperature is the most frequently measured process variable in almost all industrial sectors from the chemical industry to glass and ceramics, refrigeration and power generation. During many manufacturing processes, continuous temperature control is an important part of product quality assurance and a matter of avoiding malfunctions or detecting them at an early stage. Measuring points can be located at different places such as in containers, pipe systems, machines, ovens or reactors, whereby different gaseous, liquid or solid media, for instance, steam, water, oil or special chemical substances may be involved. In view of these extremely complex tasks, flexibility is one of the most important requirements for measurement technology and signal processing. And this is where thermocouples, which can be adapted to almost all measuring tasks due to their simple design, become relevant. The basic design and operating principle of thermocouples are described in this paper; issues relating to calibration, traceability and measurement uncertainty are addressed. Recent developments to improve temperature measurement with thermocouples are presented. New, drift-optimised thermocouples, novel designs and alternative calibration methods are described, and their advantages over conventional thermocouples or calibration methods are specified.

A New Position Calibration Method for MUSER Images

The Mingantu Spectral Radioheliograph (MUSER), a new generation of solar dedicated radio imaging-spectroscopic telescope, has realized high-time, high-angular, and high-frequency resolution imaging of the Sun over an ultra-broadband frequency range. Each pair of MUSER antennas measures the complex visibility in the aperture plane for each integration time and frequency channel. The corresponding radio image for each integration time and frequency channel is then obtained by inverse Fourier transformation of the visibility data. However, the phase of the complex visibility is severely corrupted by instrumental and propagation effects. Therefore, robust calibration procedures are vital in order to obtain high-fidelity radio images. While there are many calibration techniques available—e.g., using redundant baselines, observing standard cosmic sources, or fitting the solar disk—to correct the visibility data for the above-mentioned phase errors, MUSER is configured with non-redundant baselines and the solar disk structure cannot always be exploited. Therefore it is desirable to develop alternative calibration methods in addition to these available techniques whenever appropriate for MUSER to obtain reliable radio images. In the case where a point-like calibration source contains an unknown position error, we have for the first time derived a mathematical model to describe the problem and proposed an optimization method to calibrate this unknown error by studying the offset of the positions of radio images over a certain period of the time interval. Simulation experiments and actual observational data analyses indicate that this method is valid and feasible. For MUSER’s practical data the calibrated position errors are within the spatial angular resolution of the instrument. This calibration method can also be used in other situations for radio aperture synthesis observations.

Fibre Bragg Grating Based Interface Pressure Sensor for Compression Therapy

Compression therapy is widely used as the gold standard for management of chronic venous insufficiency and venous leg ulcers, and the amount of pressure applied during the compression therapy is crucial in supporting healing. A fibre optic pressure sensor using Fibre Bragg Gratings (FBGs) is developed in this paper to measure sub-bandage pressure whilst removing cross-sensitivity due to strain in the fibre and temperature. The interface pressure is measured by an FBG encapsulated in a polymer and housed in a textile to minimise discomfort for the patient. The repeatability of a manual fabrication process is investigated by fabricating and calibrating ten sensors. A customized calibration setup consisting of a programmable translation stage and a weighing scale gives sensitivities in the range 0.4–1.5 pm/mmHg (2.6–11.3 pm/kPa). An alternative calibration method using a rigid plastic cylinder and a blood pressure cuff is also demonstrated. Investigations are performed with the sensor under a compression bandage on a phantom leg to test the response of the sensor to changing pressures in static situations. Measurements are taken on a human subject to demonstrate changes in interface pressure under a compression bandage during motion to mimic a clinical application. These results are compared to the current gold standard medical sensor using a Bland–Altman analysis, with a median bias ranging from −4.6 to −20.4 mmHg, upper limit of agreement (LOA) from −13.5 to 2.7 mmHg and lower LOA from −32.4 to −7.7 mmHg. The sensor has the potential to be used as a training tool for nurses and can be left in situ to monitor bandage pressure during compression therapy.

Quantifying and simulating carbon and nitrogen mineralization from diverse exogenous organic matters

AbstractThe potential contributions of exogenous organic matters (EOMs) to soil organic C and mineral N supply depend on their C and N mineralization, which can be assessed in laboratory incubations. Such incubations are essential to calibrate decomposition models, because not all EOMs can be tested in the field. However, EOM incubations are resource‐intensive. Therefore, easily measurable EOM characteristics that can be useful to predict EOM behaviour are needed. We quantified C and N mineralization during the incubation of 663 EOMs from five groups (animal manures, composts, sewage sludges, digestates and others). This represents one of the largest and diversified set of EOM incubations. The C and N mineralization varied widely between and within EOM subgroups. We simulated C and N mineralization with a simple generic decomposition model. Three calibration methods were compared. Individual EOM calibration of the model yielded good model performances, while the use of a unique parameter set per EOM subgroup decreased the model performance, and the use of two EOM characteristics to estimate model parameters gave an intermediate model performance (average RMSE‐C values of 32, 99 and 65 mg C g−1 added C and average RMSE‐N values of 50, 126 and 110 mg N g−1 added N, respectively). Because of the EOM variability, individual EOM calibration based on incubation remains the recommended method for predicting most accurately the C and N mineralization of EOMs. However, the two alternative calibration methods are sufficient for the simulation of EOMs without incubation data to obtain reasonable model performances.

Precision electrical power sources calibration using electrical energy and frequency standards

This paper presents an alternative method for precision electrical power sources calibration. As traditional method, the proposed method uses a power and energy standard, but also employs a frequency standard. Calibration results for both methods are discussed and their advantages are pointed out.

An alternative tree method for calibration of the local volatility

<p style='text-indent:20px;'>In this paper, we combine the traditional binomial tree and trinomial tree to construct a new alternative tree pricing model, where the local volatility is a deterministic function of time. We then prove the convergence rates of the alternative tree method. The proposed model can price a wide range of derivatives efficiently and accurately. In addition, we research the optimization approach for the calibration of local volatility. The calibration problem can be transformed into a nonlinear unconstrained optimization problem by exterior penalty method. For the optimization problem, we use the quasi-Newton algorithm. Finally, we test our model by numerical examples and options data on the S & P 500 index. Numerical results confirm the excellent performance of the alternative tree pricing model.</p>

Integrated Highway Safety Information System (HSIS) datasets by means of a Roadway Safety Data Integrator (RSDI) tool.

The datasets and tool presented in this article are related to the research article entitled “Improving crash predictability of the Highway Safety Manual through optimizing local calibration process” (Dadvar et al., 2020) [1], in which these datasets were used to investigate alternative local calibration methods for the Highway Safety Manual (HSM) [2] local application. The datasets are integrated Highway Safety Information System (HSIS) [3] state-wide rural two-lane, two-way roads (R2U) data from states of Illinois and Washington.The HSIS is a database that maintains motor vehicle crash data, roadway inventory, and traffic volume data for several US states. It is an excellent source of data to highway safety research and can be used to investigate many research questions. However, to prepare an analysis-ready roadway safety dataset based on the HSIS or any databases that store the relevant data in multiple different datasets, the researchers should integrate multiple datasets, merge or unmerge and remove certain inconsistent records, and finally clean the integrated dataset. The HSIS staff is usually accommodating and eager to help, but sometimes the nature of data needs is complicated and laborious.A tool named Roadway Safety Data Integrator (RSDI) was developed for combining, segmenting, and selecting homogeneous (unchanged during the study period for certain variables of interest) HSIS roadway segments and also crash assignment by desired crash attributes (e.g., crash severity or type). The RSDI tool can be helpful for integrating different safety-related datasets such as roadway inventory (including grade, curve, and other subsets), traffic volume, and motor vehicle crash data; also, it can do required segmentation and identify the homogeneous roadway segments over the desired years of study that are the basis for development and calibration of the HSM predictive models.The shared datasets contain homogeneous roadway segments, geometric details, and crash data for six years from Illinois (2005–10) and Washington (2010–15). The datasets and RSDI tool would be important sources generally for investigating highway safety research questions and in particular, for HSM-related analyses. The RSDI tool can be used for similar purposes and it is not limited to the HSIS data. It can be used for segmentation and finding homogeneous segments of any datasets that follow linear referencing.The datasets and RSDI tool are hosted in the Mendeley Data repository [4].

Calibrating stereo-digital image correlation system using synthetic speckle-pattern calibration target

We describe an alternative stereo calibration method for stereo-digital image correlation (stereo-DIC) using computer-simulated speckle-pattern calibration targets and a DIC-based control points matching technique. The present work refines and extends the recently proposed camera calibration method to stereo calibration, which is an essential part of stereo-DIC measurement. In the proposed calibration method, the calibration target is generated by displaying a synthetic speckle pattern on a commercial tablet. On the simulated speckle pattern, a group of control points is specified with flexible location and number, which is further precisely matched to the captured calibration images using the well-developed subset-based DIC algorithm. These precisely matched control points are subsequently used to calibrate the intrinsic and extrinsic parameters of the stereo-DIC system with stereo calibration algorithm. For better accuracy, the error in the manufacture of the calibration target is also considered and compensated. As a flexible number of control point matches are registered with high accuracy and strong robustness, the presented stereo calibration method using synthetic speckle pattern calibration target offers higher calibration accuracy than that based on a calibration target with a limited number of designated features, such as checkerboard target and circular point target. After being demonstrated by a set of simulated calibration tests, the proposed stereo calibration method was applied to calibrate a real stereo-DIC system, which was then used to measure 3D full-field shapes and displacements. The results confirm the effectiveness and accuracy of the proposed stereo calibration method for stereo-DIC applications.

Improvement of heliostat pointing accuracy by calibration at optimized dissimilar source vectors

Almost all commercial heliostats are calibrated using the sun and a target placed below the central receiver. This setup limits the orientations that the heliostat can assume during calibration since the sun follows a restricted path. The calibration points, therefore, do not cover a wide range of heliostat orientations. This could lead to suboptimal calibration.This paper investigates the improvement in calibration that is possible when a heliostat’s orientation covers a wider range. In practice, this is possible by placing artificial light sources throughout the heliostat field.The investigation is done using only numerical simulations. Simulations make it possible to pinpoint the sources of poor pointing accuracy, which is difficult to achieve for physical heliostats.The results show that there is around a 10% improvement in pointing accuracy when using the alternative calibration method.

Improving crash predictability of the Highway Safety Manual through optimizing local calibration process

The predictive method of the Highway Safety Manual (HSM) estimates crash frequency by applying an uncalibrated safety performance function (SPF) and a set of uncalibrated crash modification factors (CMFs) to each location individually; then the predicted crashes must be adjusted by a local calibration factor (LCF) at the aggregate level for at least 30–50 sites per SPF. Although this calibration procedure assures total predicted crashes will be localized, still the prediction of crashes for individual locations suffers from the aggregate localization process. An alternative approach of locally calibrating the HSM predictive method is proposed to improve prediction quality at individual locations while maintaining equality of total observed and total predicted crashes.The methodology incorporates multiple calibration factors for different components of the predictive method (SPF parameters and CMFs) rather than a single calibration factor as recommended by the HSM that only calibrates at the aggregate level. In the proposed method, the application of calibration factors expressed in both weight and power function better reflects the local conditions while still ensuring calibration at the aggregate level. The parameters are estimated through an optimization process of five different methods.Rural two-lane, two-way roads (R2U) data was used from the states of Maryland, Illinois, and Washington. A tool named “Roadway Safety Data Integrator (RSDI)” was developed for data preparation. Different Goodness-of-Fit measures along with CURE plots indicated that the proposed method performed significantly better than the HSM calibration method, calibration function (that will most likely be calibration process in the HSM 2nd edition), calibrated Washington models (for the case of Washington data), and some alternative calibration methods suggested by past studies. Moreover, the results indicated that the additional parameters for CMFs could improve the prediction significantly; a previous study did not find this to be so due to data limitations, but we have improved the methodology and are not so limited. Application of the proposed approach can lead to more accurate identification of hot-spots and site-specific strategies. Considering the limitations of this study, some avenues for further research are discussed.

The Multivariate Kyle Model: More is Different

We reconsider the multivariate Kyle model in a risk-neutral setting with a single, perfectly informed rational insider and a rational competitive market maker, setting the price of $n$ securities. We prove the unicity of a symmetric, positive definite solution for the impact matrix and provide insights on its interpretation. We explore its implications from the perspective of empirical market microstructure and argue that it provides a sensible inference procedure to cure some pathologies encountered in recent attempts to calibrate cross-impact matrices. As an illustration, we determine the empirical cross-impact matrix of US Treasuries and compare the results with recent alternative calibration methods.

Neodymium determination in hard drive disks magnets using different calibration approaches for wavelength dispersive X-ray fluorescence

Due to matrix effects and limitations in the calibration process for direct analysis of solids, the search for different calibration approaches is very important. This study is aimed to Nd determination in high-performance magnets from hard disk using direct solid analysis by wavelength dispersive X-ray fluorescence. Three univariate calibration methods were evaluated: multi-energy calibration, one-point gravimetric standard addition and two-point calibration transfer. These strategies employ an efficient matrix-matching method, minimizing the matrix effects related to the direct analysis of solids. The trueness values were calculated according to reference concentration by inductively coupled plasma optical emission spectrometry and the concentration obtained by univariate models. For almost all samples, the trueness values were within an acceptable range from 80 to 120%. Besides that, relative standard deviation values ranged from 3 to 27% for all cases and, the standard error ranged from 2 to 6% w w−1 Nd among the calibration methods. These parameters show the potential of these alternative calibration methods over traditional ones.

Camera calibration using synthetic random speckle pattern and digital image correlation

Accurate camera calibration is of fundamental importance to various vision-based 3D metrological techniques. Despite camera calibration methods using regular planar calibration targets (e.g., checkerboard or circular pattern) have been widely adopted, their accuracy is less-than-desirable due to the limited number and the low registration accuracy of control points. This work presents an alternative calibration method that uses a calibration target based on a synthetic random speckle pattern. Specifically, a set of regularly distributed control points is first specified on the synthetic speckle pattern displayed on a monitor. These control points are then precisely matched to their counterparts on the captured calibration images using the state-of-the-art digital image correlation (DIC) algorithm. Compared with the existing camera calibration methods, the proposed method possesses the advantages of much more effective control points, higher control point match accuracy, which lead to more accurate and precise estimation of camera parameters. To evaluate the performance of the proposed calibration method, simulated calibration tests using images with varied noise levels and real calibration tests were performed on the planar calibration targets using speckle, circular and checkerboard patterns. The influences of various DIC calculation parameters (i.e. the number of control points and the subset size) on calibration results are also studied using noiseless simulated images. The reprojection errors on synthetic noiseless images and real images are computed as 0.004 and 0.038 pixels, respectively, confirming the high calibration accuracy delivered by the proposed method.