A knowledge-based intelligent system for surface texture (virtual surf)

The presented thesis documents the investigation and development of the mathematical foundations for a novel knowledge-based system for surface texture (VitualSurf system). This is the first time that this type of novel knowledge-based system has been tried on surface texture knowledge. It is important to realize that surface texture knowledge, based on new generation Geometrical Product Specification (GPS) system, are considered to be too theoretical, abstract, complex and over-elaborate. Also it is not easy for industry to understand and implement them efficiently in a short time. The VirtualSurf has been developed to link surface function, specification through manufacture and verification, and provide a universal platform for engineers in industry, making it easier for them to understand and use the latest surface texture knowledge. The intelligent knowledge-base should be capable of incorporating knowledge from multiple sources (standards, books, experts, etc), adding new knowledge from these sources and still remain a coherent reliable system. In this research, an object-relationship data model is developed to represent surface texture knowledge. The object-relationship data model generalises the relational and object orientated data models. It has both the flexibility of structures for entities and also good mathematical foundations, based on category theory, that ensures the knowledge-base remains a coherent and reliable system as new knowledge is added. This prototype system leaves much potential for further work. Based on the framework and data models developed in this thesis, the system will be developed into implemental software, either acting as a good training tool for new and less experienced engineers or further connecting with other analysis software, CAD software (design), surface instrument software (measurement) etc, and finally applied in production industries.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An approach to ontology for institutional facts in the semantic web

Consiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

An approach to ontology for institutional facts in the semantic web

Refinement in software engineering allows a specification to be developed in stages, with design decisions taken at earlier stages constraining the design at later stages. Refinement in complex data models is difficult due to lack of a way of defining constraints, which can be progressively maintained over increasingly detailed refinements. Category theory provides a way of stating wide scale constraints. These constraints lead to a set of design guidelines, which maintain the wide scale constraints under increasing detail. Previous methods of refinement are essentially local, and the proposed method does not interfere very much with these local methods. The result is particularly applicable to semantic web applications, where ontologies provide systems of more or less abstract constraints on systems, which must be implemented and therefore refined by participating systems. With the approach of this paper, the concept of committing to an ontology carries much more force

An approach to ontology for institutional facts in the semantic web

This paper shows how it is possible to represent the complex data structures needed to support electronic commerce applications in the semantic web using ontologies. The conventional mereological or subtype-oriented refinement of the ontology is supplemented by a method of coordinated refinement based on category theory. The combined methods make ontologies a much more powerful tool for organising the semantic web.