Sistem Pakar Untuk Mendiagnosa Penyakit Hati Menggunakan Metode Forward Chaining

Requirement for rapid and precise information from a medical specialist in internal medicine is required. This has encouraged the development of an expert system application for liver disease is made. Expert system for diagnosing liver diseases was designed as a tool for diagnosing liver disease with knowledge base. Knowledge base obtained from several sources, is through interviews and books. This expert system used development method is problem identification, design, system design, coding, testing and implementation. Knowledge base compiled into a database with multiple tables. As the main table is diagnosis table or conclusion. Inference in an expert system uses a forward chaining method. The programming language used JSP (Java Server Pages), as for database uses SQL Server database. This expert system will show a selection of symptoms, which every symptoms would lead to a further choice to get the symptoms of the illness conclusions, solutions and explanation

Modelling Uncertainty in Physical Database Design

Physical database design can be marked as a crucial step in the overall design process of databases. The outcome of physical database design is a physical schema which describes the storage and access structures of the stored database. The selection of an ecient physical schema is an NP-complete problem. A signi cant number of eorts has been reported to develop tools that assist in the selection of physical schemas. Most of the eorts implicitly apply a number of heuristics to avoid the evaluation of all schemas. In this paper, we present an approach, based on the Dempster-Shafer theory, that explicitly models a rich set of heuristics |used for the selection of an ecient physical schema | into knowledge rules. These rules may be loaded into a knowledge base, which, in turn, can be embedded in physical database design tools.

A framework for a computer aided design system for product oriented manufacturing systems

In this paper we present a framework and an associated support system for the design of Product Oriented Manufacturing Systems (POMS). This includes the characterization and description of the structure and components of the support system, including database, user interface and knowledge base. The framework components are integrated into an organized system called CADS_POMS (Computer Aided Design System for POMS)

The devices, experimental scaffolds, and biomaterials ontology (DEB): a tool for mapping, annotation, and analysis of biomaterials' data

The size and complexity of the biomaterials literature makes systematic data analysis an excruciating manual task. A practical solution is creating databases and information resources. Implant design and biomaterials research can greatly benefit from an open database for systematic data retrieval. Ontologies are pivotal to knowledge base creation, serving to represent and organize domain knowledge. To name but two examples, GO, the gene ontology, and CheBI, Chemical Entities of Biological Interest ontology and their associated databases are central resources to their respective research communities. The creation of the devices, experimental scaffolds, and biomaterials ontology (DEB), an open resource for organizing information about biomaterials, their design, manufacture, and biological testing, is described. It is developed using text analysis for identifying ontology terms from a biomaterials gold standard corpus, systematically curated to represent the domain's lexicon. Topics covered are validated by members of the biomaterials research community. The ontology may be used for searching terms, performing annotations for machine learning applications, standardized meta-data indexing, and other cross-disciplinary data exploitation. The input of the biomaterials community to this effort to create data-driven open-access research tools is encouraged and welcomed.Preprin

Design and construction of maintainable knowledge bases through effective use of entity-relationship modeling techniques

The use of an accepted logical database design tool, Entity-Relationship Diagrams (E-RD), is explored as a method by which conceptual and pseudo-conceptual knowledge bases may be designed. Extensions to Peter Chen\u27s classic E-RD method which can model knowledge structure used by knowledge-based applications are explored. The use of E-RDs to design knowledge bases is proposed as a two-stage process. In the first stage, and E-RD, termed the Essential E-RD, is developed of the realm of the problem or enterprise being modeled. The Essential E-RD is completely independent of any knowledge representation model (KRM) and is intended for the understanding of the underlying conceptual entities and relationships in the domain of interest. The second stage of the proposed design process consists of expanding the Essential E-RD. The resulting E-RD, termed the Implementation E-RD, is a network of E-RD-modeled KRM constructs and will provide a method by which the proper KRM may be chosen and the knowledge base may be maintained. In some cases, the constructs of the Implementation E-RD may be mapped directly to a physical knowledge base. Using the proposed design tool will aid in both the development of the knowledge base and its maintenance. The need for building maintainable knowledge bases and problems often encountered during knowledge base construction will be explored. A case study is presented in which this tool is used to design a knowledge base. Problems avoided by the use of this method are highlighted, as are advantages the method presents to the maintenance of the knowledge base. Finally, a critique of the ramifications of this research is presented, as well as needs for future research

Knowledge-based control of an adaptive interface

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations

A knowledge-based decision support system for roofing materials selection and cost estimating: a conceptual framework and data modelling

A plethora of materials is available to the modern day house designer but selecting the appropriate material is a complex task. It requires synthesising a multitude of performance criteria such as initial cost, maintenance cost, thermal performance and sustainability among others. This research aims to develop a Knowledge-based Decision support System for Material Selection (KDSMS) that facilitates the selection of optimal material for different sub elements of a roof design. The proposed system also has a facility for estimating roof cost based on the identified criteria. This paper presents the data modelling conceptual framework for the proposed system. The roof sub elements are modelled on the Building Cost Information Service (BCIS) Standard Form of Cost Analysis. This model consists of a knowledge base and a database to store different types of roofing materials with their corresponding performance characteristics and rankings. The system s knowledge is elicited from an extensive review of literature and the use of a domain expert forum. The proposed system employs the multi criteria decision method of TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution), to resolve the materials selection and optimisation problem. The KDSMS is currently being developed for the housing sector of Northern Ireland

DATABASE ACCESS REQUIREMENTS OF KNOWLEDGE-BASED SYSTEMS

Knowledge bases constitute the core of those Artificial Intelligence programs which have come to be known as Expert Systems. An examination of the most dominant knowledge representation schemes used in these systems reveals that a knowledge base can, and possibly should, be described at several levels using different schemes, including those traditionally used in operational databases. This chapter provides evidence that solutions to the organization and access problem for very large knowledge bases require the employment of appropriate database management methods, at least for the lowest level of description -- the facts or data. We identify the database access requirements of knowledge-based or expert systems and then present four general architectural strategies for the design of expert systems that interact with databases, together with specific recommendations for their suitability in particular situations. An implementation of the most advanced and ambitious of these strategies is then discussed in some detail.Information Systems Working Papers Serie

Automated selection of topographic base information for thematic maps

Modern GIS are capable of producing well designed maps but offer little assistance to users with little cartographc knowledge. Maps which are produced by such users may have a lot of cartographic errors and be of poor design. Thus, it is very necessary to build cartographic knowledge into GIS to help users to make effective use of such programs and produce basic maps conforming to basic principles of design. One possible way of improving map design in GIS is to build cartographic knowledge into the system. One particular area where such cartographic knowledge could be applied is in the selection of base (topographic) information for special topic maps. The selection will depend upon map topic, map purpose, map scale, and the amount of detail required for the particular map. A topographic database at 1:250 000 has been used to starting point for this study and the scale of output maps limited to the 1:250 000 to 1:1000 000 range. To build a knowledge base of map content, published maps have been examined, and two aspects have been considered: maps with the same topic at different scales; and maps at the same scale but with different topics. For further development to the knowledge base, a questionnaire has been sent to cartographers and expert map users to determine what they consider should be the map content for maps on a range of topics at several scales. An initial examination of the knowledge base produced from the survey of published mapping highlights some anomalies, but by using the knowledge of the cartographers and map users, the knowledge base is revised. To apply this knowledge, a formula for selecting appropriate base information is tested and the results show that the approach does produce satisfactory results. It is suggested this is implemented within a GIS to allow users to focus on the analysis data, with maps produced having appropriate base information depending on the topic, scale and the required level of detail automatically