The need for text generation

For a variety of systems, such as expert systems, database systems, and problem-solving systems, text generation is one way for the system to communicate effectively with its users. This is particularly true when the system is likely to be used by a wide range of users with varying levels of expertise and background. In this paper I will show why explanation is a crucial feature of expert systems, how text generation can be used within database systems to familiarize users with the database, and where text generation can aid communication with problem-solving systems. Given that text generation is more than just a frill for such systems, a second focus of the paper will be on the kinds of problems that any designer of a text generation system must address. Some of the problems include being able to decide what to say, how to organize that information, and how to express it in natural language

Implementation and characteristics of rule-based system for the finite element analysis

Journal ArticleIt it well known that the analysis of process for the finite element method is tedious and errorprone steps. Considering the importance of the task of engineering analyses, such as structural analysis, heat transfer, fluid flow simulation, and electromagnetic potential, many researchers have tried to develop better and easier systems. Meanwhile, expert systems have been developed in various areas, such as DENDRAL, MYCIN, and XCON. There are two main reasons for developing expert systems. First, an expert system can facilitate the dissemination of vital knowledge to a certain organization with a reasonable cost. Second, an expert system does not suffer from humahpFoblems such as confusion to that it can apply appropriate rules to the problem. It is obvious that development of an expert system for finite element mesh generation can save both time and money in the finite element analysis process. A rule-based system for optimal finite element mesh generation, EFEM has been developed and implemented in powerful interactive solid modeler. Because required knowledge is translated into rules, it is not required to know detail information about the finite element analysis processes or computer science to test structural analysis. The implementation of the EFEM has been analyzed

Expert system decision support for low-cost launch vehicle operations

Progress in assessing the feasibility, benefits, and risks associated with AI expert systems applied to low cost expendable launch vehicle systems is described. Part one identified potential application areas in vehicle operations and on-board functions, assessed measures of cost benefit, and identified key technologies to aid in the implementation of decision support systems in this environment. Part two of the program began the development of prototypes to demonstrate real-time vehicle checkout with controller and diagnostic/analysis intelligent systems and to gather true measures of cost savings vs. conventional software, verification and validation requirements, and maintainability improvement. The main objective of the expert advanced development projects was to provide a robust intelligent system for control/analysis that must be performed within a specified real-time window in order to meet the demands of the given application. The efforts to develop the two prototypes are described. Prime emphasis was on a controller expert system to show real-time performance in a cryogenic propellant loading application and safety validation implementation of this system experimentally, using commercial-off-the-shelf software tools and object oriented programming techniques. This smart ground support equipment prototype is based in C with imbedded expert system rules written in the CLIPS protocol. The relational database, ORACLE, provides non-real-time data support. The second demonstration develops the vehicle/ground intelligent automation concept, from phase one, to show cooperation between multiple expert systems. This automated test conductor (ATC) prototype utilizes a knowledge-bus approach for intelligent information processing by use of virtual sensors and blackboards to solve complex problems. It incorporates distributed processing of real-time data and object-oriented techniques for command, configuration control, and auto-code generation

Integrated knowledge acquisition from text, previously solved cases, and expert memories

Within the model-based knowledge engineering framework, an integrated knowledge acquisition method was developed for a complex real-world domain with different traces of expertise. By having an expert constructively explain the previously solved cases with more general information from other traces of expertise (text, expert memories) a model-centered knowledge base is constructed. The proposed method allows for an early knowledge verification where the relevance, sufficiency, redundancy, and consistency of knowledge are already assessed at an informal level. The early knowledge verification efficiently prepares the consecutive knowledge formalization. Through a cognitively adequate model of expertise and the explanation-oriented knowledge elicitation procedures, user friendly second generation expert systems may be developed

The model-based construction of a case-oriented expert system

Second generation expert systems should be based upon an expert\u27s high level understanding of the application domain and upon specific real world experiences. By having an expert categorize different types of relevant experiences and their components, hierarchies of abstract problems and operator classes are determined on the basis of the expert\u27s accumulated problem solving experiences. The expert\u27s global understanding of the domain is integrated with the experiences by a model of expertise. This model postulates problem classes at different levels of abstractions and associated skeletal plans. During a consultation with the expert system previously unseen types of input may be used to delineate a new problem. The application of the expert system can thus be situated in changing environments and contexts. With increasing dissimilarity between the cases that were analyzed during knowledge acquisition and the specific problem that is processed at the time of the application of the system, its performance gracefully degrades by supplying a more and more abstract skeletal plan. More specifically, the search space which is represented by the skeletal plan increases until the competence of the system is exceeded. This paper describes how such a case-oriented expert system is developed for production planning in mechanical engineering

Development and Evaluation of an Expert System Approach to Uneven-Aged Management of Loblolly-Shortleaf Pine Stands in the West Gulf Region.

Forest managers expend significant time and effort seeking, organizing, and synthesizing information relevant to making effective forestry decisions. Oftentimes, they must rely on the knowledge and experience of human experts, a resource that is in short supply, requires many years to acquire, and is concentrated in a few individuals. This research task suggests expert systems as one viable solution to the problems of technology transfer and automating and maintaining expertise in consistent and usable form. Expert systems are practical computer programs which solve problems that were previously considered only solvable by human expertise. The expert system developed in this research, named FOREX, was written in ProLog. FOREX is primarily a second-generation expert system for prescribing silvicultural systems. Aside from human expertise stored in its knowledge base, FOREX is linked with growth and yield and optimization models to complement the search for optimal recommendation. A methodology was developed for transforming available literature/research information and the private knowledge of human experts into decision rules. Factors pertinent to prescribing silvicultural systems were identified. English-like decision rules were developed, and human experts were then asked to verify and confirm these rules. The process of encoding these rules into ProLog format was an important phase of the development process. In a modified Turing test, nine human evaluators rated prescriptions from four other human experts, FOREX, and another computer-based model. FOREX\u27s scores were found comparable to the research foresters and superior to the industrial foresters and the other computer model. These results indicate that human expertise, in uneven-aged management of loblolly-shortleaf pine stands, has been captured by an expert system. Success in this project should encourage other researchers to apply this approach for other forestry problems

Second generation knowledge based systems in habitat evaluation.

Many expert, or knowledge-based, systems have been constructed in the domain of ecology, several of which are concerned with habitat evaluation. However, these systems have been geared to solving particular problems, with little regard paid to the underlying relationships that exist within a biological system. The implementation of problem-solving methods with little regard to understanding the more primary knowledge of a problem area is referred to in the literature as 'shallow', whilst the representation and utilisation of knowledge of a more fundamental kind is termed 'deep'. This thesis contains the details of a body of research exploring issues that arise from the refinement of traditional expert systems methodologies and theory via the incorporation of depth, along with enhancements in the sophistication of the methods of reasoning (and subsequent effects on the mechanisms of communication between human and computer), and the handling of uncertainty. The approach used to address this research incorporates two distinct aspects. Firstly, the literature of 'depth', expert systems in ecology, uncertainty, and control of reasoning and related user interface issues are critically reviewed, and where inadequacies exist, proposals for improvements are made. Secondly, practical work has taken place involving the construction of two knowledge based systems, one 'traditional', and the other a second generation system. Both systems are primarily geared to the problem of evaluating a pond site with respect to its suitability for the great crested newt (Triturus cristatus). This research indicates that it is possible to build a second-generation knowledge-based system in the domain of ecology, and that construction of the second generation system required a magnitude of effort similar to the firstgeneration system. In addition, it shows that, despite using different architectures and reasoning strategies, such systems may be judged as equally acceptable by endusers, and of similar accuracy in their conclusions. The research also offers guidance concerning the organisation and utilisation of deep knowledge within an expert systems framework, in both ecology and in other domains that have a similar concept-rich nature

A Study on Skilled Manpower of Baby Boomers

This study aims to explore the retirement and second life plan for skilled manpower in baby boomer generation. They charges a large portion of population cohort, however, also likely to be vulnerable social group after their retirement. Therefore, it is a very important task to find plan to support the second life for them and to suggest policy plans for effective utilization of these skilled manpower. For this, literature review, statistics analysis and case study were used to realize the general situation of retirement and career paths of skilled manpower of baby boomers. Several expert meetings and on-the-spot visits were held to collect opinions and voices from the parties concerned. In addition, as a summary of research, policy seminar was held to gather the opinions about the possibility to apply systems and strategies in practice