Expert systems characterization

Evidence of the appHcation of computers and expert systems to instmmental data interpretation is found in the new discipline of chemometrics (qv) where the relationship between data and information sought is explored as a problem of mathematics and statistics (7—10). One of the most useful insights provided by chemometrics is the realization that a cluster of measurements of quantities only remotely related to the actual information sought can be used in combination to determine the information desired by inference. Thus, for example, a combination of viscosity, boiling point, and specific gravity data can be used to a characterize the chemical composition of a mixture of solvents (11). The complexity of such a procedure is accommodated by performing a multivariate data analysis. 

Today, analytical evaluation is done on a large scale in a computerized way by means of data bases and expert systems (Sect. 8.3.6). In particular, a library search is a useful tool to identify pure compounds, confirm them and characterize constituents in mixtures. Additionally, unknown new substances may be classified by similarity analysis (Zupan [1986], Hippe [1991], Warr [1993], Hobert [1995]). The library search has its main application in such fields where a large number of components has to be related with large sets of data such as environmental and toxicological analysis (Scott [1995], Pellizarri et al. [1985]). 

General. We have studied the characterization of multicomponent materials by combining modem analytical instrumentation with a commercially available AI expert system development tool. Information generated from selected analytical databases may be accessed using TIMM, ( The Intelligent Machine Model, ) available from General Research Corp., McLean, VA. This Fortran expert system shell has enabled development of EXMAT, a heuristically-1inked network of expert systems for materials analysis. 

Development of a linked network of expert systems, EXMAT, has been described for application to materials characterization. Selected instrumentation which are common to modern laboratories generate databases that are treated and interpreted within an analytical strategy directed toward a desired goal. Extension to other problem-solving situations may use the same format, but with specialized tools and domain-specific libraries. Importantly, a chemometrician s expertise has been embedded into EXMAT through access to information derived from a linked expert system,... 

An integrated GC/IR/MS instrument is a powerful tool for rapid identification of thermally generated aroma compounds. Fourier transform infrared spectroscopy (GC/IR) provides a complementary technique to mass spectrometry (MS) for the characterization of volatile flavor components in complex mixtures. Recent improvements in GC/IR instruments have made it possible to construct an integrated GC/IR/HS system in which the sensitivity of the two spectroscopic detectors is roughly equal. The combined system offers direct correlation of IR and MS chromatograms, functional group analysis, substantial time savings, and the potential for an expert systems approach to identification of flavor components. Performance of the technique is illustrated with applications to the analysis of volatile flavor components in charbroiled chicken. 

Aparicio, R. (1988) Characterization of foods by inexact rules The SEXIA expert system. J. Chemometr. A, 3, 175-192. 

Aparicio, R. and Alonso, V. (1994) Characterization of virgin olive oils by SEXIA expert system. Prog. 

A Data Procurement for Knowledge-based Systems Progress in analytical characterization of catalysts plays an important role in their further development and improvement. Synergistic effects of complimentary characterization tools by which different properties of the catalytic materials arc determined are claimed to be beneficial in catalyst design. If this is so, then an expert system for assisting in catalyst selection should be designed in such a way that it accounts for different chemical and physico-chemical properties and their relation to catalytic performance of solid materials. 

EIS data extrapolation, uses neural networks to train on electrochemical impedance spectroscopy data for extrapolation Filter debris analysis (FDA) expert system, condition monitoring of aircrafts GENERA, generic problem-solving framework for characterizing corrosion and materials problems LipuCor, prediction of corrosion in oil and gas systems... 

In terms of practical application, expert systems overlap with systems for deriving and applying quantitative structure-activity relationship (QSAR) models or equations, and with systems using artificial neural networks (ANN) or genetic algorithms. The expert systems described in this chapter are characterized by their use of a generalized store of knowledge. 

Analytical Approaches and Expert Systems in the Characterization of Microelectronic Devices... 

Even though technological advances might Improve the resolution of some of our Instrumentation, miniaturization itself will only complicate our ability to characterize devices In the future. Artificial intelligence and expert systems appear to have an excellent potential for enhancing our problem solving ability. It Is expected that with proper development, this tool could become an essential Item In the microanalyst s repertoire of techniques In tomorrow s technology. 

X-ray phase analysis is used for identification of mineral phases of rocks, soils, clays, or mineral industrial material. The phase analysis of clays is particularly difficult because these materials generally consist of a mixture of different phases, like mixed and individual clay minerals, and associated minerals, such as calcite and quartz. Placon and Drits proposed an expert system for the identification of clays based on x-ray diffraction (XRD) data [45]. This expert system is capable of identifying associated minerals, individual clay minerals, and mixed-layer minerals. It can further approximate structural characterization of the mixed-layer minerals and can perform a structural determination of the mixed-layer minerals by comparison of experimental x-ray diffraction patterns with calculated patterns for different models. The phase analysis is based on the comparison of XRD patterns recorded for three states of the sample dried at room temperature, dried at 350°C, and solvated with ethylene glycol. 

Expert System for the Characterization of Rock Types (ESCORT) is an expert system based on Bayesian rules providing probabilities for the occurrence of rock types based on geochemical and nongeochemical data. 

The use of expert systems [13-14] allows the solution of problems which lack reliable mathematical models and are characterized by a great amount of empirical knowledge acquired in heterogeneous ways and by a high level of abstraction. The study of corrosion phenomena has such characteristics and is a very promising field for the realization of expert systems. 

The process of characterizing a complex solid via a truly multitechnique analytical approach has been examined, case studies like the one described above providing valuable information. The result is a general outline for the CACSS project which we will describe in some detail here. It reflects our basic ideas about how to proceed through the analytical process in the optimum way, guided by an expert system when appropriate. 

In proportion to the importance of the catalyst materials, experimental information on their synthesis, characterization and catalytic properties are accumulating over the years. Databases of such information could be generated and further expert system approach can be applied to optimally utilize this information for the catalyst design. Relations between the observations and inferences are expressed as mathematical expressions. These independent and interdependent mathematical expressions which relate observations to the inferences are used in the decision-making steps for predictions. Finally the recent achievements in the human interfacing technology with computers - for e g., one can talk to the molecules simulated in computer, command their motions just by waving his hands, etc. have to be seen to be believed. 

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