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This is the second part of the effort to resolve the following two problems that badly need an answer: how can an appropriate theoretical foundation be chosen for modern mathematics and computer science? And, under what interpretations can modern mathematics and the theory of computer science be kept as completely as possible?

The paper sets out the foundation for the system.

Here, the logical foundation for the mathematical system of potential infinities is given.

The logical calculus, which will be used as the tool of deduction in the PIMS, is established. This new tool of reasoning is a modification of the classical two‐value logical calculus system.

Expert systems technology as an area of artificial intelligence is coming to the field of structural mechanics. A number of expert systems have been developed or are under development. This paper consists of two parts. A brief discussion of the basics of expert systems and their concepts is given in the first part. The second part reviews the prototype of expert systems developed as an aid for finite element analysis and design optimization. Twelve different expert systems are described. A partial list of books on expert systems in general is given in the Appendix.

Today the garment industry in México is vulnerable to complex problems. This type of industry is subject to influences which over time, modify the perceptions of those involved in the design process due to the fact that they face problems that have both objective and subjective characteristics. In this study the authors used interviews, direct observation methodology, and theoretical argumentation to obtain the experts knowledge as they describe the problems that arise in the process of garment design for Mexican markets. The purpose of this paper is to generate a methodology so that the expert in this field will become highly specialized, resulting in heightened abilities and reinforcing them with the methodology of soft systems and the design management model (DMM). The results suggest that they are applicable to any area of design.

The success or failure of expert system (ES) depends directly on the acquisition of knowledge (Méndez-Gurrola, 2007, 2012), to accomplish that, three large groups of techniques are used to extract that knowledge: manual, semiautomatic, and automatic. Within the group of manual techniques, interviews, protocol analysis, questionnaires, direct on site observation, and the extraction of closed curves are emphasized. This technique is chosen for its ability to extract the particular type of knowledge being sought. The knowledge of the dominion expert in the design process applied to the clothing industry in México is based on processes and at the same time is episodic, meaning that part of the procedure is automated and each step of the process triggers the next. This knowledge is also based on experience which is of an autobiographical nature.

First, when one simulates human behavior, the hardest thing is to choose a knowledge representation that conforms as closely as possible to its emulation. According to, choosing a given type of knowledge representation is an art that is discovered little by little. And this is true as one designs and assembles a representation, when one realizes how far the authors are from imitating the design of the human brain processes, and discovers or invents methodologies to achieve it, combining the results of investigations into knowledge representation, cognitive psychology, and cognitive engineering. Second, solving any complex situation in the design process function of the clothing industry is no easy task. It requires plenty of experience in the manufacturing process. One needs the ability to identify the signals emitted by complex situations, and being able to stop them in time before they create irreversible damage. By merging the soft system methodology (SSM) and DMM with the experts’ abilities and knowledge (the result being the EXITUS model (EM)), makes knowledge modeling possible. A problem cannot be solved if it is unknown, if the problem persists and grows it becomes more complex. By describing a problem, based on: its origin, its relationship, and its effects, it also confers the ability to solve it. Thereby, an SBC with the characteristics presented in this paper, not only improves the design process function as a whole, it also contributes to achieving corporate success. Finally, it influences directly on: a quality product; market positioning; and good economic results. First, the SBC-EXITUS was tested and endorsed by expert management designers. When a designer identifies a complex problem using the SBC-EXITUS system, he is capable of verifying its existence with facts and real life situations. This enables quicker decision making decisions, which saves time and money, due to the fact that a non-desirable state of affairs may be contemplated in advance. Fourth, in this project an SBC named SBC-EXITUS has been implemented using the SSM and the DMM, with the purpose of detecting possible problems in the design process of the clothing industry. Its implementation is developed by the use of production rules. Fifth, utilizing the methodology and the production rules like knowledge representation technique, make possible to acquire dominion knowledge in complex problems as in the study case clothing industry in México. This approach is also applicable to other areas of design.

Utilizing the methodology and the production rules like knowledge representation technique, make possible to acquire dominion knowledge in complex problems as in the study case clothing industry in México. This approach is also applicable to the garment industry in the international context, as well as to other areas of design such as architecture, furniture, and others. The EM is a generic methodology. In this research and case, it has been applied in a design process within the garment industry, specifically in a case in Mexico. Yet this does not limit its use in a different context and problem situation. Having in mind the difference between countries in aspects such as sponsoring, technology, worker skills, marketing, etc. the tools for diagnostics in the Appendix 2, may be adapted to each context with enriched questions directed to specific aspects involved. Every new application allows facts and production rules that make the use of ES more efficient.

The ES-EXITUS was tested and endorsed by expert management designers. When a designer identifies a complex problem using the ES-EXITUS, he is capable of verifying its existence with facts and real life situations. This enables quicker decision making decisions, which saves time and money, due to the fact that a non-desirable state of affairs may be contemplated in advance.

Solving any complex situation in the design process function of the clothing industry is no easy task. It requires plenty of experience in the manufacturing process. One needs the ability to identify the signals emitted by complex situations, and being able to stop them in time before they create irreversible damage. By merging the SSM and DMM with the experts’ abilities and knowledge (the result being the EM), makes knowledge modeling possible. A problem cannot be solved if it is unknown, if the problem persists and grows it becomes more complex. By describing a problem, based on: its origin, its relationship and its effects, it also confers the ability to solve it. Thereby, an SBC with the characteristics presented in this paper, not only improves the design process function as a whole, it also contributes to achieving corporate success. Finally, it influences directly on a quality product, market positioning, and good economic results.

Describes an approach to real‐time expert systems for integrated network management. Presents an overview of expert systems technology, proceeding to develop the requirements for a real‐time system in network management. Describes a system being developed (1989) by Pacific Bell. Describes NETREX, a prototype real‐time system, aimed at automatically maintaining Pacific Bell′s internal data networks. Concentrates on an application for solving problems with travel tickets in real time.

The purpose of this paper is to explain the development and testing of a condition‐monitoring sub‐module of an integrated plant maintenance management application based on artificial intelligence (AI) techniques, mainly knowledge‐based systems, having several modules, sub‐modules and sections.

The approach is applicable to general purpose machinery. A maintenance knowledge base is developed from published information on maintenance management like handbooks, journals, conference proceedings, because of difficulty in accessing expert knowledge and information on actual machine problems, from experts in maintenance management. The knowledge‐based engine comprises intelligent algorithms and software‐generated pop‐ups/alerts/alarms predictive tools. The expert system on an off‐line basis, on a failure in the plant's machinery or deterioration in performance, will trigger fault diagnosis to detect the reason and give immediate advice to the maintenance group.

Knowledge‐based intelligent machine troubleshooting/maintenance software enables maintenance technicians to refer to custom‐made, ready‐to‐use and easily upgradable maintenance software. Its benefits include: reduction in machine down‐time, reduction in skill level for maintenance activities, ease of maintenance, speedy response and affordable cost. The paper collectively deals with the analysis of the state‐of‐the‐art expert systems for diagnosis and maintenance of general‐purpose industrial machinery.

The software is essentially for general purpose industrial machinery (stand‐alone type) applications. For continuously operating machinery, the software has to be altered to accommodate continuous data through strategically mounted sensors.

Knowledge based, ready‐to‐use, custom‐built, maintenance management software application having many modules and sub‐modules on various aspects of modern maintenance practices has direct application for shopfloor maintenance.

A part of fully‐fledged maintenance management application based on AI principles is discussed in the present paper. Its benefits include: use of latest methodology – AI techniques for maintenance field, ready‐to‐install condition, vast and immediate access to maintenance management information, user‐friendly and interactive modules, easily upgradable features for the application.

To discuss systemic thinking in relation to the naturalistic and anti‐naturalistic position in the philosophy of social science. To develop the theme in two parts: I and II.

A cybernetic approach is taken and a discussion on what is the foundation for the philosophy of social science for systemic thinking is developed.

The findings for Part I are that the rationalistic view of knowledge is based on reflection and reason. The empirical viewpoint on knowledge based on observations. The realistic view of knowledge is based on the link between the rationalistic and the empirical point of view. The systemic viewpoint is based on the realistic view of knowledge.

Provided assistance to social scientists who study social systems from the systemic or cybernetic point of view. Gives researchers studying problems/phenomena in social systems a systemic viewpoint.

It positioned systemic thinking in relation to the philosophy of social science.

In this paper we propose a new method for the creation of subject bibliographies. Our method consists of two phases: first, the raw bibliographical material is downloaded from an online bibliographical database (e.g. DIALOG), and then this material is processed using knowledge‐based means. We apply a meta‐programming approach in which the raw bibliographic material is viewed as a logic program upon which we develop a second‐order logic program. The second‐order program creates the subject bibliography by operating a rule base and the first‐order logic program. The entire system, named REX, was written in PROLOG and used to create automatically a subject bibliography on Applications of Logic Programming in Decision and Control.

The event‐driven paradigm is appropriate for context aware, distributed applications, yet basic events may be too low level to be meaningful to users. The authors aim to argue that this bottom‐up approach is insufficient to handle very low‐level sensor data or to express all the queries users might wish to make.

The authors propose an alternative model for querying and subscribing transparently to distributed state in a real‐time, ubiquitous, sensor‐driven environment such as is found in Sentient Computing.

The framework consists of four components: a state‐based, temporal first‐order logic (TFOL) model that represents the concrete state of the world, as perceived by sensors; an expressive TFOL‐based language, the Abstract Event Specification Language (AESL) for creating abstract event definitions, subscriptions and queries; a higherorder service (Abstract Event Detection Service) that accepts a subscription containing an abstract event definition as an argument and in return publishes an interface to a further service, an abstract event detector; and a satisfiability service that applies classical, logical satisfiability in order to check the satisfiability of the AESL definitions against the world model, in a manner similar to a constraint‐satisfaction problem.

The paper develops a model‐based approach, appropriate for distributed, heterogeneous environments.

This paper presents an approach inspired by the Functional Grammar (fg) of S.C. Dik, which has been rethought to adapt it to the context of automatic analysis of bureaucratic documents. The research is part of a larger ongoing project for the automated processing of land registry documents and the model presented has been demonstrated for automatic content analysis of documents concerning technical operations of real estate (division and regrouping of lots) and is to be extended also to mortgages. The first paragraphs examine the theoretical principles of the application; the process of understanding the document content through the production of predications is then presented and the content analysis strategy briefly sketched.

The purpose of this paper is to present a framework for the articulation of relationships between collection-level and item-level metadata as logical inference rules. The framework is intended to allow the systematic generation of relevant propagation rules and to enable the assessment of those rules for particular contexts and the translation of rules into algorithmic processes.

The framework was developed using first order predicate logic. Relationships between collection-level and item-level description are expressed as propagation rules – inference rules where the properties of one entity entail conclusions about another entity in virtue of a particular relationship those individuals bear to each other. Propagation rules for reasoning between the collection and item level are grouped together in the framework according to their logical form as determined by the nature of the propagation action and the attributes involved in the rule.

The primary findings are the analysis of relationships between collection-level and item-level metadata, and the framework of categories of propagation rules. In order to fully develop the framework, the paper includes an analysis of colloquial metadata records and the collection membership relation that provides a general method for the translation of metadata records into formal knowledge representation languages.

The method for formalizing metadata records described in the paper represents significant progress in the application of knowledge representation techniques to problems of metadata creation and management, providing a flexible technique for encoding colloquial metadata as a set of statements in first-order logic. The framework of rules for collection/item metadata relationships has a range of potential applications for the enhancement or metadata systems and vocabularies.