Interpretation problems

In analysis of homopolymers the critical interpretation problems are calibration of retention time for molecular weight and allowance for the imperfect re >lution of the GPC. In copolymer analysis these interpretation problems remain but are ven added dimensions by the simultaneous presence of molecular weight distribution, copolymer composition distribution and monomer sequence length distribution. Since, the GPC usu y separates on the basis of "molecular size" in solution and not on the basB of any one of these particular properties, this means that at any retention time there can be distributions of all three. The usual GPC chromatogram then represents a r onse to the concentration of some avera of e h of these properties at each retention time. 

The purpose of this paper is to propose solutions to the GPC interpretation problems fitting the needs of high conversion polymerization kinetic modelling. 

The two interpretation problems involved are (A) calibration and (B) correction of imperfect resolution caused by axial dispersion. 

MSD provides molecular weight, fragmentation information and mass selectivity. Also, simultaneous GC-MS/MIP-AES has been described, using both a low-pressure and an atmospheric-pressure splitter [336]. The combination of MS and AED data sets provides the potential for application to a wide range of analytical problems, such as screening for the presence of hetero-atom-containing analytes (AED), identification and confirmation (MS) and quantification (MS, AED). On-line LVI-GC-AED/MS (dual detection) has been described with small (i.e. less than 0.5 s) differences in retention time of a compound with AED and MS detection [67], The dual-hyphenation set-up largely eliminates data-interpretation problems caused by small differences in retention time, or retention indices and is,... 

General considerations of data availability lead immediately to the recognition that detection systems are more likely to be designed as comprehensive numeric-symbolic interpreters as illustrated in Fig. 3. State description systems may be configured as shown in either Fig. 3 or Fig. 4. Fault classification systems are most likely to require the symbolic-symbolic mapping to compensate for limited data as shown in Fig. 4. Many practical data interpretation problems involve all three kinds of interpreters. In all situations, there is a clear need for interpretation systems to adapt to and evolve with changing process conditions and ever-increasing experience. 

By definition, the exemplar patterns used by these algorithms must be representative of the various pattern classes. Performance is tied directly to the choice and distribution of these exemplar patterns. In light of the high dimensionality of the process data interpretation problem, these approaches leave in question how reasonable it is to accurately partition a space such as R6+ (six-dimensional representation space) using a finite set of pattern exemplars. This degradation of interpretation performance as the number of possible labels (classes) increases is an issue of output dimensionality. 

The knowledge required to implement Bayes formula is daunting in that a priori as well as class conditional probabilities must be known. Some reduction in requirements can be accomplished by using joint probability distributions in place of the a priori and class conditional probabilities. Even with this simplification, few interpretation problems are so well posed that the information needed is available. It is possible to employ the Bayesian approach by estimating the unknown probabilities and probability density functions from exemplar patterns that are believed to be representative of the problem under investigation. This approach, however, implies supervised learning where the correct class label for each exemplar is known. The ability to perform data interpretation is determined by the quality of the estimates of the underlying probability distributions. 

With the view that a KBS interpreter is a method for mapping from input data in the form of intermediate symbolic state descriptions to labels of interest, four families of approaches are described here, each offering inference mechanisms and related knowledge representations that can be used to solve interpretation problems namely, model-based approaches, digraphs, fault trees, and tables. These methods have been heavily used... 

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 decomposition and localization of the problem effectively produces a distributed set of data interpretation problems, each with a particular set... 

In this way, data interpretation is accomplished by a set of nested numeric-symbolic and symbolic-symbolic interpreters. Note that the hierarchical decomposition results in a distributed set of symbolic-symbolic interpretation problems represented by nodes. Each problem requires intermediate interpretations of numeric data as input to the symbolic-... 

Fiedel, S. (1996), Blood from stones Some methodological and interpretative problems in blood residue analysis, Archaeol. Sci. 23(1), 139-147. 

In 5, coordination through O polarizes the C = O bond producing the incipient carbonium ion, which is more susceptible to nucleophilic attack. In 6, there is intramolecular attack by coordinated OH on the N-bonded monodentate amino acid. In 7, only a small rate enhancement would be anticipated from intermolecular attack on the N-bonded monodentate. In these representations, X is OR, but anticipating the next section, it might also be NHR. These interpretive problems are illustrated in the hydrolysis of complexes of the type 8, where again any of three mechanisms corresponding to 5-7 could apply. 

One of the more important criteria in the estimation of robustness is the occurrence of different spot orders at different temperatures or relative humidities. This is called spot cross-over. A spot cross-over clearly implies a lack of resolution and an interpretation problem (which spot is which compound). The number of spot cross-overs should be minimal and preferably zero. The number of cross-overs can easily, be determined when at fixed settings the elution order on the plates is examined. 

Chromatographic interferences are extremely rare due to the high selectivity of the applied chromatographic conditions. The most difficult interpretation problems are the discrimination between secondary effects and latent porphyria (see above, Interpretation ). Therefore, the exclusion of porphyria in an asymptomatic individual requires additional measures to be taken (see below). 

Dual induction In the shallow penetration log, a higher resistivity is obtained relative to a free gas zone due to hydrate dissociation. This is a very tricky interpretation problem with Rw changing, and gas and hydrate both being insulators. The deep induction log shows high resistivity and mimics an ice-bearing reservoir. However, this log is confounded by Rw changing, and by gas and hydrate both being insulators... 

Mancinelli R, Guiducd MS (2002) Procedural aspects and interpretation problems in the analysis of drugs of abuse. Ann 1st Super Sanita 38(3) 305-313... 

OBJECTS FEATURES PROPERTY data interpretation problem... 

The following data interpretation problems address objects belonging to two or more categories ... 

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