Absolute metrics

An absolute measure is one in which a simple count of events is recorded and reported. This would include the number of occurrences of a specific type of incident per year (e.g., release, loss of containment, fire) or activity (e.g., how many employees were trained, whether a mechanical integrity evaluation was conducted). Absolute metrics do not necessarily provide information on the quality of an activity or a change or trend in the activity over time. Absolute metrics also may be difficult to compare meaningfully across the organization. However, regulatory agencies and the public may be very interested in some absolute metrics. For example, the public wants to know the number of releases from a facility and the quantity of the release—particularly from a facility in their community. However, how a given release or a facility s release record compares with facilities outside the community may be of minimal, if any, interest. 

Changes in dimensions ean be quoted as either an absolute or relative metrie. For example expansion is an absolute metric, typically quoted in pm or mm, whieh gives the movement in a specified direction strain is a relative metric, typically quoted as a percentage or fraction, which relates the expansion to an initial fixed dimension. Both of which can have their uses. However, the direction in which the expansion or strain is measured should be clearly specified, e.g., in-plane (x-y direction, parallel to the plane of the film) strain and out-of-plane (z-direction, perpendicular to the plane of the film) strain. In addition, how the strains have been calculated, e.g., relative to the as-synthesized passive length or relative to the stable length after precycling, should be clearly specified. Furthermore, it should be clearly stated whether the metric quoted is a reversible or irreversible expansion or... 

The resistance when moving one layer of liquid over another is the basis for the laboratory method of measuring absolute viscosity. Poise viscosity is defined as the force (pounds) per unit of area, in square inches, required to move one parallel surface at a speed of one centimeter-per-second past another parallel surface when the two surfaces are separated by a fluid film one centimeter thick. Figure 40.16. In the metric system, force is expressed in dynes and area in square centimeters. Poise is also the ratio between the shearing stress and the rate of shear of the fluid. 

The concept of kinematic viscosity is the outgrowth of the use of a head of liquid to produce a flow through a capillary tube. The coefficient of absolute viscosity, when divided by the density of the liquid is called the kinematic viscosity. In the metric system, the unit of viscosity is called the stoke and it has the units of centimeters squared per second. One one-hundredth of a stoke is a centistoke. 

Still other units encountered in the literature and workplace come from various other systems (absolute and otherwise). These include metric systems (c.g.s. and MKS), some of whose units overlap with SI units, and those (FPS) based on English units. The Fahrenheit and Rankine temperature scales correspond to the Celsius and Kelvin, respectively. We do not use these other units, but some conversion factors are given in Appendix A. Regardless of the units specified initially, our approach is to convert the input to SI units where necessary, to do the calculations in SI units, and to convert the output to whatever units are desired. 

Consideration of the white blood cell (WBC) and differential counts leads to another problem. The total WBC is, typically, a normal population amenable to parametric analysis, but differential counts are normally determined by counting, manually, one or more sets of one hundred cells each. The resulting relative percentages of neutrophils are then reported as either percentages or are multiplied by the total WBC count with the resulting count being reported as the absolute differential WBC. Such data, particularly in the case of eosinophils (where the distribution does not approach normality), should usually be analyzed by nonpara-metric methods. It is widely believed that relative (%) differential data should not be reported because they are likely to be misleading. 

Summation of absolute differences (I) results in an ME in which all differences have the same statistical weight. Summation of squared differences (II) is the more common practice and gives an MSE in which large deviations have higher weight than small ones. In order to make the metric independent of the number N of observations, the error sum must be related to N or an equivalent sum of the observations ... 

The generalized Fisher theorems derived in this section are statements about the space variation of the vectors of the relative and absolute space-specific rates of growth. These vectors have a simple natural (biological, chemical, physical) interpretation They express the capacity of a species of type u to fill out space in genetic language, they are space-specific fitness functions. In addition, the covariance matrix of the vector of the relative space-specific rates of growth, gap, [Eq. (25)] is a Riemannian metric tensor that enters the expression of a Fisher information metric [Eqs. (24) and (26)]. These results may serve as a basis for solving inverse problems for reaction transport systems. 

Therefore, in this approach, we develop Risk Model III as a reformulation of Risk Model II by employing the mean-absolute deviation (MAD), in place of variance, as the measure of operational risk imposed by the recourse costs to handle the same three factors of uncertainty (prices, demands, and yields). To the best of our knowledge, this is the first such application of MAD, a widely-used metric in the area of system identification and process control, for risk management in refinery planning. 

Figure 3.2 The effect of prolonged subcutaneous implantation on biosensor function. Blood glucose values shown in solid circles and glucose sensor values in the continuous lines. The early study (top panel), but not the late study (bottom), shows excellent sensor accuracy and minimal lag between blood glucose and sensed glucose values. MARD (mean absolute relative difference) refers to a sensor accuracy metric. EGA refers to the Clarke error grid analysis accuracy metric.

Distances with C = 1 are especially useful in the classification of local data as simple as in Fig. 5-12, where simply d( 1, 2) = a + b. They are also known as Manhattan, city block, or taxi driver metrics. These distances describe an absolute distance and may be easily understood. With C = 2 the distance of Eq. 5-7, the EUCLIDean distance, is obtained. If one approaches infinity, C = oo, in the maximum metric the measurement pairs with the greatest difference will have the greatest weight. This metric is, therefore, suitable in outlier recognition. 

Of the various methods that may be used to determine bioavailability for ASOs, the best refer to tissue levels as the most relevant metric for calculating an estimate of absolute bioavailability. As mentioned in Chapter 4, ASOs distribute rapidly to the tissues, with an extremely slow transfer rate back into the central circulation. In addition, the elimination of ASOs occurs predominantly by nucleases in the tissue compartment. Thus, bioavailability based on plasma concentrations does not provide an accurate estimate of absolute bioavailability for ASOs if plasma concentrations cannot be quantified at extremely low concentrations for a prolonged period of time to adequately assess systemic exposure. The direct use of tissue levels in combination with physiologic pharmacokinetic modeling, however, may allow the accurate determination of bioavailability for ASOs. 

---