Parameter Calibration

One of the limitations of the portable field survey instruments in the measurement of americium is that their quantitative accuracy depends on how well the lateral and vertical distribution of americium in the soil compares with the calibration parameters used. These methods can provide a rapid assessment of americium levels on or below surfaces in a particular environment however, laboratory-based analyses of samples procured from these environmental surfaces must be performed in order to ensure accurate quantification of americium (and other radionuclides). This is due, in part, to the strong self absorption of the 59.5 keV gamma-ray by environmental media, such as soil. Consequently, the uncertainty in the depth distribution of americium and the density of the environmental media may contribute to a >30% error in the field survey measurements. Currently, refinements in calibration strategies are being developed to improve both the precision and accuracy (10%) of gamma-ray spectroscopy measurements of americium within contaminated soils (Fong and Alvarez 1997). 

Verification is the complement of calibration model predictions are compared to field observations that were not used in calibration or fidelity testing. This is usually the second half of split-sample testing procedures, where the universe of data is divided (either in space or time), with a portion of the data used for calibration/fidelity check and the remainder used for verification. In essence, verification is an independent test of how well the model (with its calibrated parameters) is representing the important processes occurring in the natural system. Although field and environmental conditions are often different during the verification step, parameters determined during calibration are not adjusted for verification. 

Chemical parameters (e.g., partition coefficients, decay rates, temperature and moisture effects) are not usually considered as calibration parameters because they can be measured in a laboratory moreover, calibration is usually not possible due to lack of observed data. However, most scientists will agree that extrapolation of laboratory parameter measurements to field conditions is a risky assumption. If observed chemical data are available, refinement of initial chemical parameters through calibration should be considered. Errors in calibration-derived parameter values are often a function of how much calibration was performed or errors in system inputs and/or outputs. In many modeling efforts, conscientious model users will often overrun the calibration budget because of the natural tendency to continue to make calibration runs in an effort to minimize discrepancies between simulated and observed values. Parameter errors associated with calibration are more often a result of missing and/or erroneous data either as system inputs or outputs. 

On the other hand, least trimmed squares (LTS) can be used to estimate the calibration parameters that points which produce the (n — h) largest deviation squares are rejected and the remaining h points are used for the LTS fitting ... 

Instron data files which have been saved on the minicomputer can be analyzed at any time using the STRESS program. After reading the specified raw data file, the STRESS program first converts the voltages to stress values based upon the data collection rates and calibration parameters, according to Equation 1. 

This chart corresponds to the original Shewhart-chart. For tmeness control, standard solutions, synthetic samples or RM/CRM samples may be analysed. Calibration parameters (slope and intercept) can also be used in a X-chart to check the constancy of the calibration. 

It is also possible to use calibration parameters (slope, intercept) to check the plausibility of the calibration... 

Some standards or decrees include the obligatory measurement of control samples or repeated measurement. This can be used for control charts with only little effort. Other values like calibration parameters are also available without additional woik. They also can be used for control charts, especially if the stability of calibration is known to be a weak point in the procedure. 

Benoit and co-workers [18] proposed that the hydrodynamic volume, Vr which is proportional to the product of [17] and M, where [17] is the intrinsic viscosity of the polymer in the SEC eluent, may be used as the universal calibration parameter (Fig. 18.3). For linear polymers, interpretation in terms of molecular weight is straightforward. If the Mark-Houwink-Sakurada constants K and a are known, log [t7]M can be written log M1+ + log K, and VT can be directly related to M. The size-average molecular weight, Mz, is defined by this process ... 

If the measurement of LOD is not critical, an estimate can be made from the calibration parameters taking the intercept as the blank measurement and the standard error of the regression as the standard deviation of the blank. Equation (8.1) becomes... 

Equation 8.3 relies on the assumption that the calibration parameters hold to the limit of detection, which is not necessarily correct. If the calibration is taken over a very wide range, for example in some element analyses by inductively coupled plasma, the uncertainty is not constant but is proportional to the concentration. In this case it is not possible to estimate the detection limit by equation (8.3). 

Method validation covers a number of aspects of an analytical method that have already been evaluated in the course of development and use. The values of the calibration parameters must be known to use the method to analyze a particular sample, and any serious deviations from the measurement model should have been discovered. In addition, however, every method should undergo a robustness study as the practicality of the method may ultimately depend on how rugged it is. 

Calibration parameters are instrument parameters whose values do not vary with the type of experiment, such as peak widths, peak shapes, mass assignment, and resolution versus sensitivity. 

If the correct calibration parameters were used, and good calibration data were acquired, the instrument should be calibrated correctly. However, in some circumstances it is possible to meet the calibration criteria without matching the correct peaks. This situation is unusual, but it is always sensible to examine the on-screen calibration report to check that the correct peaks have been matched. These errors may occur when the following parameters are set ... 

In GPC, the product [77] M, (or the hydrodynamic radius Re) has been widely accepted as a universal calibration parameter. In the Ptitsyn-Eizner modification of the Flory-Fox equation the quantity 4>, which relates the dimensional parameters to the above product, is taken as a variable. The value of < depends upon molecular expansion in solution as represented by a function f(e). Because of this dependence polymeric species having the same [77] M value cannot have the same statistical dimensions (radius of gyration or end-to-end distance) unless they have the same e value. Thus, if [77] M is a universal calibration parameter, the statistical parameters cannot be used as such. A method is presented for obtaining the Mw/Mn ratio from GPC data even though universal calibration is used. 

Tn GPC the product [77] M has been widely accepted as a universal calibration parameter, where [77] is the intrinsic viscosity and M is the molecular weight. This product is defined by the Einstein-Simha viscosity expression (I) as... 

The calibration can be stored in Immusoft , and the next experiment can recall the calibration parameters in order to determine an unknown sample concentration when the same protocol is used. 

According to the rules of combined uncertainty evaluation [8, 9], ox can be considered as negligible, if it leads to increase of SXo for less then one-third of its initial value (calculated by ordinary least squares technique). An example of the ox influence on the calibration parameters bh b0 and SXo, and corresponding lifetime of the traceability chain are analysed below. 

Bias or imprecision associated with compromises made or lack of adequate knowledge in specifying the structure and calibration (parameter estimation) of a model. 

Maintenance history is an essential component of GxP compliance. Work instructions and SOPs controlling maintenance operations should ensure that the maintenance engineer records aU performance measures, observations, and maintenance tasks in a consistent manner with calibration records, for example, containing calibration parameters, with calibration procedure, reference to calibration equipment, name of engineer, date of calibration, next due date, etc. Where automated condition and performance monitoring is employed, the integrity of the recorded data is obviously a GxP issue. 

Analysis of the stability of the signal at constant pressure versus time reveals that the relative error in pressure for analysis periods t < 2 s is dominated by the inaccuracy of the calibration parameter Z,oeo (caused by thermal drifts during the long calibration runs) rather than vibrational contributions or thermal effects upon analysis itself Fig. 4 shows the comparison of the signals detected via the Baratron differential transducer and the... 

The remarkable situation in which we find ourselves in modem materials science is that physics has for some time been sufficiently developed, in terms of fundamental quantum mechanics and statistical mechanics, that complete and exact ab initio calculations of materials properties can, in principle, be performed for any property and any material. The term ab initio" in this context means without any adjustable or phenomenological or calibration parameters being required or provided. One simply puts the required nuclei and electrons in a box and one applies theory to obtain the outcome of a specified measurement. The recipe for doing this is known but the execution can be tedious to the point of being impossible. The name of the game, therefore, has been to devise approximations and methods that make the actual calculations doable with limited computer resources. Thanks to increased computer power, the various approximations can be tested and surpassed and more and more complex materials can be modelled. This section provides a brief overview of the theoretical methods of solid state magnetism and of nanomaterial magnetism in particular. 

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