No description available.

This research studies the process of acquiring knowledge from experts; that is, studies knowledge-acquisition methods to acquire expert knowledge. Forty subjects used a machine-aided knowledge-acquisition tool to model a word processing task. By using the tool, the subjects developed models that were on average 72.8% accurate with a baseline model of the task and 88.5 % consistent among themselves. This research makes four contributions: 1) a complete review of thirty-one knowledge-acquisition methods from manual to machine learning, 2) an evaluation methodology and metrics to evaluate knowledge-acquisition methods, 3) an evaluation of an automated knowledge-acquisition tool called Cognitive Analysis Tool (CAT) developed for this research, and 4) suggested improvements to the current version of the tool. This research describes, develops a taxonomy of, and evaluates thirty-one knowledge-acquisition methods to determine which method matches a defined set of criteria A method is chosen, extended, and automated in the form of a machine-aided knowledge-acquisition tool. The method is chosen based on five criteria including a connection between the chosen, method and the information processing model of problem solving as defined by Newell and Simon (1972). This research evaluates the performance of the tool in terms of the accuracy and consistency of the knowledge bases generated by using the tool. A baseline is derived from this study to which other knowledge-acquisition tools' performance can be compared. The evaluation methodology and metrics developed in this research can be used to evaluate other knowledge-acquisition tools. From this research, four groups of changes to the automated knowledge-acquisition tool are suggested to improve the usability and performance of the tool. The changes are suggested for the user interface and the modes of operation of the tool. / Master of Science

A derivation of the Michaelis-Menton growth kinetics model is developed to simulate batch fermentation of glucose to ethanol using yeast. / Master of Science

The design of reinforced concrete beams involves the selection of design parameters such as beam dimensions and reinforcement details which result in a safe and economical section. This process of design consists of three stages: preliminary design, structural analysis, and detailed design which includes the selection of dimensions, reinforcement, and stirrups. The design process is an iterative one where considerable judgement and experience are required. This is an ideal situation for the application of expert system technology. A knowledge based expert system called BEAMDES was developed for the flexure design of reinforced concrete beams in accordance with ACI 318-83 specifications. The expert system was developed using the micro-computer based expert system shell, Insight 2+. BEAMDES can be used to design both rectangular and tee sections. The beams can be simply supported, cantilevered, or continuous. The results obtained from BEAMDES were tested against several example problems for both supported and continuous beams. It was found that the designs recommended by the system were similar to those of the examples. / Master of Science

The selection and sizing of the components for the design of a hydrostatic transmission is a tedious process. Necessary procedures include: analyzing the load profile, choosing a suitable configuration, determining the required size of components, selecting components, evaluating the performance of selected units, and then adjusting or selecting alternate components for improved performance. A. rule-based expert system, called HSTX, was developed to aid the selection and sizing of the major components-- pump, motor, and final drive-- of a hydrostatic transmission. Four types of options were considered. For the first, output speed and torque are both constant. For the second, horsepower output is constant at different speeds. For the third type, the output torque is constant at different speeds. For the last, torque and horsepower outputs can vary over a wide range of speeds. The program selects one of the four combinations of fixed pump and fixed motor, fixed pump and variable motor, variable pump and fixed motor, or variable pump and variable motor to match the desired outputs. The HSTX program includes databases which contain the specifications of hydraulic pumps and motors from selected manufacturers. HSTX interactively prompts the user to enter basic problem constraints and performance requirements. The program then recommends system configuration and selects components from the databases to meet the performance requirements specified. To assist inexperienced designers, HSTX is designed in such a way that the program gives easily understood hints, explanations, and guidance. The program, HSTX, can analyze the load profile, size the components, select available components from a database, evaluate the performance, and output the final results. Trial runs with different operators indicate that HSTX can be effectively used by a designer with a background in hydraulic systems but with little background in HST design. / Master of Science

Testing programs with tractable algorithms is one area in which software engineers have made numerous advances over the past few decades. Testing rule-based expert systems, however, is a new area in software engineering which requires new testing techniques. For the most part, traditional software engineering testing strategies assume modular program development. This assumption is impractical to make for expert system development, for the knowledge base of an expert system is quite simply a huge non-modular program. It consists almost entirely of non-ordered, multi-branching decision statements. In traditional programming, the module interfaces are limited and well defined. For rule-based expert systems, the interaction among rules is combinatoric and highly data-driven. Thus, the testing of a completed expert system via traditional path analysis is impractical. The design of a testing strategy for expert systems focuses on the generic phases of expert system development. Briefly, these phases include system definition, incremental system implementation, and system maintenance.. Using this simplified breakdown of the expert system development process as a guide, certain testing techniques can be generalized enough to work for any expert system application. / Master of Science

Knowledge based systems are currently the most marketable products of Artificial Intelligence research. The process of developing a knowledge based system can be very time consuming and costly. This thesis provides an automated, structured, knowledge acquisition methodology for accelerated development of knowledge based systems. This constrained approach leads to considerable savings in development costs, and results in a modular system that is easy to maintain. The system acts as a design consultant' to help the expert in elucidating his knowledge to the end-users. / Master of Science

This research investigated the development of a prototype expert system to allocate manpower in service systems. The three expert system components - a global data base, a knowledge base, and a inference procedure - were built for application in different service facilities. The general service system constraint set was used in conjunction with an expert's allocation logic to specify the production rules within the prototype expert system's knowledge base. The sequencing of these production rules is controlled by the inference procedure. The protoype system can be applied in those service facilities that maintain similar service system constraints as the facility used in this research. A specific facility was used to demonstrate and analyze the prototype expert system. An allocation schedule generated by the expert system was compared to a manually generated schedule. Full-time manpower allocations were the same. Yet, part-time manpower allocations differed due to flexibility, availability and shift constraints. The user must evaluate the expert system's schedule and make reassignments where necessary. Thus, this research determined that an expert system can be utilized to allocate manpower in service facilities; however, further research is required to build an expert system that encompasses all service facilities. / M.S.

A "causal" expert system based on hypothetical reasoning and its application to a Mark 45 turret gun's lower hoist are described. HOIST is a system that performs fault diagnosis without the use of a domain expert or "shallow rules". Rather its "knowledge" is coded directly from a structural specification of the Mark 45 lower hoist. The technology reported here for assisting the lesser acquainted diagnostician differs considerably from the normal rule-based expert system techniques: it reasons about machine failures from a functional model of the device. In a mechanism like the lower hoist, a functional model must reason about forces, fluid pressures and mechanical linkages, that is, qualitative physics. HOIST technology can be directly applied to any exactly specified device for modeling and diagnosis of single or multiple faults. Hypothetical reasoning, the process embodied in HOIST, has general utility in qualitative physics and reason maintenance. / Master of Science

No description available.