Development of a Universal Measurement Process Framework

Calibration software has largely been developed with a direct measurement comparison method at the forefront. While adequate for many routine calibration processes, over time this approach becomes insufficient for more complex calibrations and often leads to the creation of special tests, add-ons, and various types of workarounds which are neither ideal nor sustainable over the long term. In some cases, these inadequacies initiate the development of a completely new and separate calibration software designed to specifically address a single calibration discipline or measurement problem. This paper discusses a complete and universal measurement process framework which is not only capable of accommodating routine and complex calibration scenarios alike, but also allows the use of various comparisons such as direct, indirect, ratio, differential, transfer, and substitution measurement comparison techniques. Additionally, the framework generates a comprehensive set of records to include; all original observations, calculations, corrections, conversions, environmental factors, and measurement results, allowing for step-by-step auditing of every measurement performed. Although primarily intended for use within calibration software which can facilitate automated, semi-automated, and manual calibrations - this approach may also be utilized entirely outside of software in any calibration scenario

FastTomo: A SerialEM Script for Collecting Electron Tomography Data

FastTomo is a SerialEM script for collecting tilted specimen images in transmission electron microscopes to be further used in tomographic reconstruction. It achieves a speedup over conventional tracking methods by minimizing the usage of off-target tracking shots, and instead applies proportional control to the specimen images. Movement in the Z coordinate is estimated prior to each tilt series in a separate calibration routine. Overall, this method is fast and reliable when the field of view is at least 1 um, and can tolerate minor errors in setting eucentric height. The implemented tilt series schemes include the unidirectional, bidirectional, and dose-symmetric schemes.

Quantitative Determination of Vitamins A and E in Ointments Using Raman Spectroscopy

A quantitative analysis of vitamins A and E in commercial ointments containing 0.044% and 0.8% (w/w) of active pharmaceutical ingredients, respectively, was performed using partial least squares models based on FT Raman spectra. Separate calibration systems were prepared to determine the amount of vitamin A in a petrolatum base ointment and to quantify vitamins A and E in a eucerin base one. Compositions of the laboratory-prepared and commercial samples were controlled through a principal component analysis. Relative standard errors of prediction were calculated to compare the predictive ability of the obtained regression models. For vitamin A determination, these errors were found to be in the 3.8–5.0% and 5.7–5.9% ranges for the calibration and validation data sets, respectively. In the case of vitamin E modeling, these errors amounted to 3.7% and 4.4%. On the basis of elaborated models, vitamins A and E were successfully quantified in two commercial products with recoveries in the 99–104% range. The obtained data indicate that the Raman technique allows for accurate analysis of the composition of semisolid formulations in their native state, including low dose preparations.

Improvement of Hargreaves–Samani Reference Evapotranspiration Estimates with Local Calibration

Improving irrigation water management is an important asset when facing increased water shortages. The Hargreaves–Samani (HS) method is a simple method that can be used as an alternative to the Penman–Monteith (PM) method, which requires only temperature measurements for estimating reference evapotranspiration (ETo). However, the applicability of this method relies on its calibration to local meteorological specificities. The objective of this study was to investigate the effects of local calibration on the performance of the HS equation. The study was carried out for the middle portion of the São Francisco River Basin (MSFB), Brazil, and considered four calibration approaches: A1—single calibration for the entire MSFB; A2—separate calibration by clusters of months; A3—by clusters of stations; and A4—for all contexts resulting by combining A2 and A3. Months from the wet season showed larger improvements by the calibration of the HS model, since mean air temperature and its daily range showed stronger correlations to ETo. On the other hand, the months from the dry season and stations from the eastern region of MSFB performed poorly regardless of the calibration approach adopted. This occurred because, in those cases, ETo presented larger correlation to variables that are missing in the HS equation, and the use of the full PM equation seems unavoidable.

The importance of a device specific calibration for smartphone colorimetry

In order for a smartphone-based colorimetry system to be generalizable, it must be possible to account for results from multiple phones. A move from device-specific space to a device independent space such as XYZ space allows results to be compared, and means that the link between XYZ values and the physical parameter of interest needs only be determined once. We compare mapping approaches based on calibration data provided in image metadata, including the widely used open-source software dcraw, to a separate calibration carried out using a colorcard. The current version of dcraw is found to behave suboptimally with smartphones and should be used with care for mapping to XYZ. Other metadata approaches perform better, however the colorcard approach provides the best results. Several phones of the same model are compared and using an xy distance metric it is found that a device-specific calibration is required to maintain the desired precision.

A Comparison of the Separate and Concurrent Calibration Methods for the Full-Information Bifactor model

When calibrating items using multidimensional item response theory (MIRT) models, item response theory (IRT) calibration programs typically set the probability density of latent variables to a multivariate standard normal distribution to handle three types of indeterminacies: (a) the location of the origin, (b) the unit of measurement along each coordinate axis, and (c) the orientation of the coordinate axes. However, by doing so, item parameter estimates obtained from two independent calibration runs on nonequivalent groups are on two different coordinate systems. To handle this issue and place all the item parameter estimates on a common coordinate system, a process called linking is necessary. Although various linking methods have been introduced and studied for the full MIRT model, little research has been conducted on linking methods for the bifactor model. Thus, the purpose of this study was to provide detailed descriptions of two separate calibration methods and the concurrent calibration method for the bifactor model and to compare the three linking methods through simulation. In general, the concurrent calibration method provided more accurate linking results than the two separate calibration methods, demonstrating better recovery of the item parameters, item characteristic surfaces, and expected score distribution.

Application of Highway Safety Manual Method for Ramp Crash Prediction to Loop and Diamond Ramps

The AASHTO Highway Safety Manual (HSM) now includes crash prediction procedures for ramps. Research was undertaken to assess how well these new crash prediction methods represented the safety performance of two ramp types with distinctly different geometrics: loop ramps and diamond ramps. The HSM crash prediction procedures were applied to 235 loop ramps and 243 diamond ramps in two states—California and Washington—and the results were compared with 5 years of actual crash data for the same ramps. The results indicate that the HSM crash prediction method can be applied to both loop and diamond ramps, but to compare the safety performance of these two ramp types properly, separate calibration of loop and diamond ramps is needed.

Recursive PLS Modeling of Aromatics and Olefins in Gasoline

The separate calibration models of aromatics and olefins were established for gasoline through recursive partial least square (R-PLS) method in this paper.The some oil refining enterprise application has achieved better effect on the software being realized by R-PLS method. The calibration models were validated through comparison of the results determined by fluorescent indicator adsorption (FIA) and near infrared spectroscopy (NIR) methods.The NIR analysis results were well coincident with those of FIA method.The NIR can not only raise the analysis efficiency and lower the analysis cost,but also has better precision compared with FIA method.