Insight 2+ expert system

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. 

This is a fairly mundane exchange. You would not need years of experience before you were able to decide for yourself where you should go on a holiday, so there is little commercial potential for an expert system advising overworked biologists on how to spend their summer break. Nevertheless, this simple interaction gives us an early insight into how an expert system appears to the user. The system has provided one half of a conversation, eliciting information from the user through a sequence of focused questions as... 

There is much concern about the length of time required to develop expert systems, particularly since so many have achieved various stages of prototype, but few have been completed. Our experience with SpinPro has led to many insights, more than can be fully discussed here. Nevertheless, a few major points are worth mentioning. 

Computer-aided trend identification offers potential benefits, but is dependent on the quality of the input information. Expert systems and artificial intelligence are tools being tested. When successful, they may give improved insight into identifying common causes and trend analyses. 

Conventional algorithms, commercial software, or solution approaches are not available. Scientific problems often arise from new analytical results and insights. Many of the problems to be solved resulting from new findings are rarely covered by literature, not to mention software algorithms. Rule-based systems are one of the alternatives for an easier development of expert systems. 

Overview. The CORA expert system has gone through two major phases in its development. The first-phase deliverable was a prototype system. The knowledge bases and explanation facility were written using the Production Rule Language (PRL) of Insight 2+. Additional user interface and reporting capabilities were developed in dBASE III+ and Nantucket Clipper. 

In the second phase of the project, EPA wanted to distribute the model to the EPA regions for independent use, and CORA was refined and upgraded to facilitate that use. The expert system was revised to include four knowledge bases containing 671 rules and up to 40 technologies for recommendation. Insight 2+, whose name was changed to Level 5 dBASE III+ and the Nantucket Clipper compiler were used. 

To meet these constraints, we chose for our development tool Insight 2+, a rule-based and microcomputer-based expert system shell that met most of the criteria of a good tool, as described by Waterman (2)—that is, it has good user interface, rule-tracing, and debugging capabilities. In addition, Insight 2+ has no requirements for licensing fees. 

The objectives of catalyst design are to improve the catalytic performance, defined by lifetime, selectivity, and activity, Utilization of data bases and expert systems will continue to be the first step and will develop towards the application of new information sciences. Chemistry of the catalytic process is playing an important practical role in industry. The integration with molecular and material science is a natural extension. The molecular science approach is now able to provide insight into structures and mechanisms at the atomic level. 

The reaction center has either to be spedfied when inputting a reaction into a database, or it has to be determined automatically. Specification on input is time-consuming but it can benefit from the insight of the human expert, particularly so if the reaction input is done by the primary investigator as is the case in an electronic notebook. Automatic determination of reaction centers is difficult, particularly so when incomplete readion equations are given where the stoichiometry of a reaction is not balanced see Section 3.1). One approach is to try first to complete the stoichiometry of a reaction equation by filling in the missing molecules such as water, N2, etc. and then to start with reaction center determination. A few systems for automatic reaction center specification are available. However, little has been published on this matter and therefore it is not discussed in any detail here. 

Modern science is very different from the descriptions of early systems of thought. Early philosophers and theorists lacked the objective methodologies and rational investigative processes required for the controlled experiments that led to modern science. They were more concerned with seeking universal cures for sickness, transmutation of base metals into gold, and mysticism in general. Most, but not all, ancient philosophers depended more on the written words of experts than on their own observations and insights. 

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