Data interpretation applications

The front-end and back-end boundaries on each analysis and interpretation component can be defined so that a particular approach or methodology can be determined based on the specific mapping requirements. Practical data interpretation applications often involve the integration of multiple technologies as required by these three distinct forms of data mapping. This... 

Within the framework of the ANDES (Automatic Non-Destructive Evaluation System) at TNO Institute of Applied Physics two prototype applications have been developed for automated NDT data interpretation - both using the CBR methodology. 

The widespread use of packaged units of all sizes requires interpretation of catalogue data by applications engineers, sales engineers, and others, and by the end user. 

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,... 

Nonlinear methods based on linear projection also can be used for data interpretation. Since these methods require numeric inputs and outputs, the symbolic class label can be converted into a numeric value for their training. Proposed applications involving numeric to symbolic transformations have a reasonably long history (e.g., Hoskins and Himmel-... 

J. T. Watson and O. D. Sparkman, Introduction to Mass Spectrometry Instrumentation, Applications, and Strategies for Data Interpretation, 4th Edition, Chichester, Wiley, 2007. 

Single-molecule detection in confocal spectroscopy is characterized by an excellent signal-to-noise ratio, but the detection efficiency is in general very low because the excitation volume is very small with respect to the whole sample volume, and most molecules do not pass through the excitation volume. Moreover, the same molecule may re-enter this volume several times, which complicates data interpretation. Better detection efficiencies can be obtained by using microcapillaries and micro structures to force the molecules to enter the excitation volume. A nice example of the application of single-molecule detection with confocal microscopy is... 

A principal components multivariate statistical approach (SIMCA) was evaluated and applied to interpretation of isomer specific analysis of polychlorinated biphenyls (PCBs) using both a microcomputer and a main frame computer. Capillary column gas chromatography was employed for separation and detection of 69 individual PCB isomers. Computer programs were written in AMSII MUMPS to provide a laboratory data base for data manipulation. This data base greatly assisted the analysts in calculating isomer concentrations and data management. Applications of SIMCA for quality control, classification, and estimation of the composition of multi-Aroclor mixtures are described for characterization and study of complex environmental residues. 

There are several applications to scientific and engineering instrumentation which especially relevant to chemistry and chemical engineering. These include building into instruments expertise in instrument control and data interpretation, to attempt to minimize the amount of staff time required to perform routine analyses and to optimize the performance of a system. There are several efforts underway in process control, focused currently in the electrical power and chemical industries. 

The correlations with data on gas phase reactions have served to establish that the parameters calculated by our methods are indeed useful for the prediction of chemical reactivity data. Their application is, however, not restricted to data obtained in the gas phase. This has been shown through a correlation of pK values (in H O) of alcohols with residual electronegativity and polarizability parameters, by including a parameter that is interpreted to reflect steric hindrance of solvation ( ),... 

The application of quantitative automated mineralogy in enhancing geochemical data interpretation in mineral exploration and metaliurgical processes... 

For example, a single estimate for total PCB s has been historically collected in the NHATS program. Current advances in chemical analysis protocols now allow for the determination of isomer specific resolution of PCB s. Given the 209 PCB s that are now possible to detect, an adequate evaluation of the data without the use of pattern recognition techniques seems impossible. From a QA/QC perspective, these methods can facilitate the detection of outliers and aid in the interpretation of human chemical residue data. The application of statistical analysis must keep abreast with these advances made in chemisty. To handle the complexity and quantity of such data, the use of more sophisticated statistical analyses is needed. 

The advent of analytical techniques capable of providing data on a large number of analytes in a given specimen had necessitated that better techniques be employed in the assessment of data quality and for data interpretation. In 1983 and 1984, several volumes were published on the application of pattern recognition, cluster analysis, and factor analysis to analytical chemistry. These treatises provided the theoretical basis by which to analyze these environmentally related data. The coupling of multivariate approaches to environmental problems was yet to be accomplished. 

Additional evidence for the applicability of the above data interpretation is obtained by using Equation 3 to predict values of l/(Tlp) min. These are 2.8 X 104 sec-1 and 6.4 X 103 sec-1 for H = 4.7 G and 20.6 G, respectively, and are consistent with the T p and T2 data. The motional properties reported here differ significantly from previous measurements the activation energy obtained from a temperature above 120°C is two to three times the values obtained in Ref. 13, and motional narrowing of the lineshape occurs at a significantly higher temperature than that in Ref. 12. 

All this basic information has set the stage for bioremediation as an inexpensive and effective approach for cleaning contaminated soils, waters, and sediments. Considerable efforts are currently underway to develop the necessary field application techniques that make this a wholesale commercial reality. However, the complexities of the biodegradation processes involved make the efforts challenging if not, in some cases, frustrating. This is especially true for larger-scale field studies because increased variability and heterogeneity Cause difficulties in data interpretation. 

Tn the previous papers of this series (1, 2, 3, 4) calibration and repro- ducibility of gel permeation chromatography (GPC) have been extensively examined. This paper describes the application of GPC to two selected samples of linear polyethylenes, one having a narrow molecular weight distribution (NMWD) and another a broad molecular weight distribution (BMWD). These samples were distributed by the Macro-molecular Division of IUPAC (5) for the molecular characterization of commercial polymers. The average molecular weights by GPC are compared with the data obtained from infrared spectroscopy, osmotic pressure, melt viscosity, and intrinsic viscosity. Problems associated with data interpretation are discussed. 

In the chemical engineering domain, neural nets have been applied to a variety of problems. Examples include diagnosis (66,67), process modeling (68,69), process control (70,71), and data interpretation (72,73). Industrial application areas include distillation column operation (74), fluidized-bed combustion (75), petroleum refining (76), and composites manufacture (77). 

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