Interpretative approach

At another level, certain KBS approaches provide the mechanisms for decomposing complex interpretation problems into a set of smaller, distributed and localized interpretations. Decomposition into smaller, more constrained interpretation problems is necessary to maintain the performance of any one interpreter and it makes it possible to apply different interpretation approaches to subparts of the problem. It is well recognized that scale-up is a problem for all of the interpretation approaches described. With increases in the number of input variables, potential output conclusions, complexity of subprocess interactions, and the spatial and temporal distribution of effects, the rapidity, accuracy, and resolution of interpretations can deteriorate dramatically. Furthermore, difficulties in construction, verification, and maintenance can prohibit successful implementation. 

The second property in Equation 4.5 normalizes p(r) to the total number of electrons in the system by integrating over the whole 3D space. Note that in atomic units (used throughout this chapter unless otherwise mentioned), the number density p(r) becomes the electronic charge density, thereby paving the way to various useful, interpretative approaches as described below. 

For the evolution of somanmbule BewuBtsein, see E. Bauer, Spiritismus und Okkultismus, in Loers, 60-80. As with Cubism, Futurism, and Dadaism, so too with modernist art made by chance a wholly new interpretive approach is called for, namely an exploration of the historical sources of esoteric automatism (I am working on that particular lacuna). 

There are two general types of aerosol source apportionment methods dispersion models and receptor models. Receptor models are divided into microscopic methods and chemical methods. Chemical mass balance, principal component factor analysis, target transformation factor analysis, etc. are all based on the same mathematical model and simply represent different approaches to solution of the fundamental receptor model equation. All require conservation of mass, as well as source composition information for qualitative analysis and a mass balance for a quantitative analysis. Each interpretive approach to the receptor model yields unique information useful in establishing the credibility of a study s final results. Source apportionment sutdies using the receptor model should include interpretation of the chemical data set by both multivariate methods. 

The Information provided by these models Is circumstantial In nature and the results from a single Interpretive approach at this stage of model evolution may be Insufficient to develop the level of confidence required to support strong action or clear decisions. The objective of source apportionment studies must be to build a strong enough bridge of circumstantial Information (Figure 3) to quantitatively relate a source to an Impact. Thus, the entire Information base must support and be Internally consistent with a study s conclusions to provide decision makers with confidence that their actions will result In Improved air quality. 

The interpretation stage consists of applying one or all of the chemical receptor model approaches to interpreting the chemical data generated. The objective of a source apportionment study is the support of effective control action. The level of confidence required to initiate this action may be established with a single receptor model interpretive approach or it may require information from additional interpretive approaches, wind sector analysis, (, ... 

Each interpretive approach to the receptor model yields unique information useful in establishing the credibility of the final results. 

A disadvantage of simple interpretive methods is that the model to which the retention data (or other data) are fit must be fairly accurate. In other words, an interpretive approach may fail if one or more sample components exhibits anomalous retention. Although rare in SFC, such retention behavior is observed occasionally and is difficult to predict intuitively. Note, however, that by anomalous retention we do not mean behavior that is merely unusual, e.g., retention that decreases smoothly with increasing density (at constant temperature). Retention that varies in a regular (continuous) manner, even if unusual, can usually be modeled with a high degree of accuracy (vide infra). 

Although it is beyond the scope of this chapter, more sophisticated interpretive methods can be employed to compensate for the anomalous retention behavior. That is, the complex retention surfaces are broken down into smaller parts in an iterative fashion the smaller retention surfaces are more accurately modeled by simple functions. This iterative interpretive approach has recently been applied in micellar LC (MLC) for the optimization of organic modifier, surfactant concentration, and pH (57,58). 

Table VI. Regression Coefficients (Equation 9) of Individual Compounds in the Eight-Component Mixture to be Optimized by the Interpretive Approach...

An alternative interpretive approach is to leave the human biomonitoring result as is but develop applied dose-biomarker relationships in animals. That requires obtaining animal PK data to support PBPK modeling or the collection of animal biomarker information in study designs that mimic key toxicology datasets. 

Additional Case Studies Used to Exemplify Interpretative Approaches Described in Chapter 5... 

Irrespective of the interpretative approach, it is now widely recognised that many enzymes do show marked deviations from Michaelis-Menten behaviour, and the deviation is often interpretable in terms of regulatory function in vivo. Thus, for example, a number of enzymes, including threonine deaminase [30] and aspartate transcarbamylase [31] as textbook cases, show a sigmoid, rather than hyperbolic dependence of rate upon substrate concentration. This, like the oxygen saturation curve of haemoglobin, permits a response to changes in substrate concentration... 

We did not search and cannot claim rmiversal gen-eralizability about our findings concerning tripartism, industrial relations and safety. The objective was of an exploratory kind to see and interpret tripartism and safety work as part of ongoing work systems, a task which demands an interpretive approach. In a next phase, it seems wise to follow up on this study with a more wide-ranging, quantitative approach. 

Hnatyshyn S, Sanders M, Shipkova P, Luk E, Warrack B, Reily M, Poster 375 Automated Mass Spectra Interpretation Approach to Data Reduction for LC-MS Metabonomics Analysis, Poster presented at the American Society for Mass Spectrometry Conference, June 5, Denver, CO, 2008... 

Due to the problem of the unintended interpretation of item 6 for KU students, a slightly revised test structure of two factors measured by seven items without item 6 was considered for the purpose of interpretation. CFA was performed and Cronbach s alpha determined for each data set without item 6 to support this new score interpretation approach. As shown in Table 4, the model fits for the three data sets are all tenable without item 6. The model fit for KU improved when item 6 was removed. For the WU and the SE data, the model fit without item 6 remains good based on accepted fit criteria. For KU, the new Cronbach s alpha is 0.78 for the scale of intellectual accessibility and 0.77 for the scale of emotional satisfaction. The final Cronbach s alphas are 0.86 and 0.84 for the WU data and 0.80 and 0.79 for the SE data. All values are above the satisfactory level of 0.7. 

For these reasons, the foregoing interpretation approaches to estimating nutrient requirements do not apply to energy. 

Prosser, M., Trigwell, K. Taylor, P. (1994) A phenomenographic study of academics conceptions of science learning and teaching. Learning and Instruction, 4 (3), 217-231. Sandberg, J. (2000) Understanding human competence at work An interpretive approach . 

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