868 resultados para Knowledge acquisition (Expert systems)


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This work deals with quality level prediction in concrete structures through the helpful assistance of an expert system wich is able to apply reasoning to this field of structural engineering. Evidences, hypotheses and factors related to this human knowledge field have been codified into a Knowledge Base in terms of probabilities for the presence of either hypotheses or evidences,and conditional presence of both. Human experts in structural engineering and safety of structures gave their invaluable knowledge and assistance necessary when constructing the "computer knowledge body".

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Knowledge acquisition and model maintenance are key problems in knowledge engineering to improve the productivity in the development of intelligent systems. Although historically a number of technical solutions have been proposed in this area, the recent experience shows that there is still an important gap between the way end-users describe their expertise and the way intelligent systems represent knowledge. In this paper we propose an original way to cope with this problem based on electronic documents. We propose the concept of intelligent document processor as a tool that allows the end-user to read/write a document explaining how an intelligent system operates in such a way that, if the user changes the content of the document, the intelligent system will react to these changes. The paper presents the structure of such a document based on knowledge categories derived from the modern knowledge modeling methodologies together with a number of requirements to be understandable by end-users and problem solvers.

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Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

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This paper analyzes the relationship between the techniques used to build expert systems and the behaviors they exhibit to show that there is not sufficient evidence to link the behavioral shortcomings of first-generation expert systems to the shallow methods of representation and inference they employ. There is only evidence that the shortcomings are a consequence of a general lack of knowledge. Moreover, the paper shows that the first-generation of expert systems employ both shallow methods and most of the so-called deep methods. Lastly, we show that deeper methods augment but do not replace shallow reasoning methods; most expert systems should possess both."

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Convergence of technologies in the Internet and the field of expert systems have offered new ways of sharing and distributing knowledge. However, there has been a general lack of research in the area of web-based expert systems (ES). This paper addresses the issues associated with the design, development, and use of web-based ES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional ES were reviewed and a knowledge engineering framework for developing them was revisited. The study considered three web-based ES: WITS-advisor - for e-business strategy development, Fish-Expert - for fish disease diagnosis, and IMIS - to promote intelligent interviews. The benefits and challenges in developing and using ES are discussed by comparing them with traditional standalone systems from development and application perspectives. © 2004 Elsevier B.V. All rights reserved.

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The initial aim of this research was to investigate the application of expert Systems, or Knowledge Base Systems technology to the automated synthesis of Hazard and Operability Studies. Due to the generic nature of Fault Analysis problems and the way in which Knowledge Base Systems work, this goal has evolved into a consideration of automated support for Fault Analysis in general, covering HAZOP, Fault Tree Analysis, FMEA and Fault Diagnosis in the Process Industries. This thesis described a proposed architecture for such an Expert System. The purpose of the System is to produce a descriptive model of faults and fault propagation from a description of the physical structure of the plant. From these descriptive models, the desired Fault Analysis may be produced. The way in which this is done reflects the complexity of the problem which, in principle, encompasses the whole of the discipline of Process Engineering. An attempt is made to incorporate the perceived method that an expert uses to solve the problem; keywords, heuristics and guidelines from techniques such as HAZOP and Fault Tree Synthesis are used. In a truly Expert System, the performance of the system is strongly dependent on the high quality of the knowledge that is incorporated. This expert knowledge takes the form of heuristics or rules of thumb which are used in problem solving. This research has shown that, for the application of fault analysis heuristics, it is necessary to have a representation of the details of fault propagation within a process. This helps to ensure the robustness of the system - a gradual rather than abrupt degradation at the boundaries of the domain knowledge.

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This thesis examines the process of knowledge acquisition by Malaysian manufacturing firms through their involvement in international strategic alliances. The strategic alliances can be with or without equity involvement. Firms involved with a foreign partner with equity involvement are joint venture firms while non-equity involvement are firms that engaged in contractual agreements. Using empirical evidence from 65 international alliances gathered through a survey conducted in high-technology manufacturing sectors, several factors that influence the process of knowledge acquisition are examined. The factors are: learning capacity, experience, goals, active involvement and accessibility to the foreign knowledge. Censored regression analysis and ordered probit analysis are used to analyse the effects of these factors on knowledge acquisition and its determinant parts, and the effects of knowledge acquisition and its determinants on the performance of the alliances. A second questionnaire gathered evidence relating to the factors, which encouraged tacit knowledge transfer between the foreign and Malaysian partners in international alliances. The key findings of the study are: knowledge acquisition in international strategic alliances is influenced by five determining factors; learning capacity, experience, articulated goals, active involvement and accessibility; new technology knowledge, product development knowledge and manufacturing process knowledge are influenced differently by the determining factors; knowledge acquisition and its determinant factors have a significant impact on the firm’s performance; cultural differences tend to moderate the effect on the firm’s performance; acquiring tacit knowledge is not only influenced by the five determinant factors but also by other factors, such as dependency, accessibility, trust, manufacturing control, learning methods and organisational systems; Malaysian firms involved in joint ventures tend to acquire more knowledge than those involved in contractual agreements, but joint ventures also exhibit higher degrees of dependency than contractual agreements; and the presence of R&D activity in the Malaysian partner encourages knowledge acquisition, but the amount of R&D expenditure has no effect on knowledge acquisition.

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This thesis describes work done exploring the application of expert system techniques to the domain of designing durable concrete. The nature of concrete durability design is described and some problems from the domain are discussed. Some related work on expert systems in concrete durability are described. Various implementation languages are considered - PROLOG and OPS5, and rejected in favour of a shell - CRYSTAL3 (later CRYSTAL4). Criteria for useful expert system shells in the domain are discussed. CRYSTAL4 is evaluated in the light of these criteria. Modules in various sub-domains (mix-design, sulphate attack, steel-corrosion and alkali aggregate reaction) are developed and organised under a BLACKBOARD system (called DEX). Extensions to the CRYSTAL4 modules are considered for different knowledge representations. These include LOTUS123 spreadsheets implementing models incorporating some of the mathematical knowledge in the domain. Design databases are used to represent tabular design knowledge. Hypertext representations of the original building standards texts are proposed as a tool for providing a well structured and extensive justification/help facility. A standardised approach to module development is proposed using hypertext development as a structured basis for expert systems development. Some areas of deficient domain knowledge are highlighted particularly in the use of data from mathematical models and in gaps and inconsistencies in the original knowledge source Digests.

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A class of intelligent systems located on anthropocentric objects that provide a crew with recommendations on the anthropocentric object's rational behavior in typical situations of operation is considered. We refer to this class of intelligent systems as onboard real-time advisory expert systems. Here, we present a formal model of the object domain, procedures for obtaining knowledge about the object domain, and a semantic structure of basic functional units of the onboard real-time advisory expert systems of typical situations. The stages of the development and improvement of knowledge bases for onboard real-time advisory expert systems of typical situations that are important in practice are considered.

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External partnerships play an important role in firms’ acquisition of the knowledge inputs to innovation. Such partnerships may be interactive – involving exploration and mutual learning by both parties – or non-interactive – involving exploitative activity and learning by only one party. Examples of non-interactive partnerships are copying or imitation. Here, we consider how firms’ innovation objectives influence their choice of interactive and/or non-interactive connections. We conduct a comparative analysis for the economies of Spain and the UK, which have contrasting innovation eco-systems and regulation burdens.

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Many Enterprise Systems (ES) projects have reported nil or detrimental impacts despite the substantial investment in the system. Having expected positive outcomes for the organization and its functions through the weighty spend, the effective management of ES-related knowledge has been suggested as a critical success factor for these ES projects in ES implementations. This paper suggests theoretical views purporting the importance of understanding on knowledge management for ES success. To explain the complex, dynamic and multifaceted of knowledge management, we adopt the concepts in Learning Network Theory. We then conceptualized the impact of knowledge management on ES by analyzing five case studies in several industries in India, based on the Knowledge-based Theory of the Firm that captures the performance of the system.

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In line with repeated recent calls for research on specific forms of growth rather than on an undifferentiated notion of “total growth,” our study contributes to the understanding of entrepreneurial growth. By this we mean growth through expansion into new geographic markets and/or via the introduction of new products or services. Building on Penrose's theory of the growth of the firm and on the research streams she has in part inspired, we investigate the impact of knowledge acquisition from international markets on entrepreneurial growth both at home and abroad. We further suggest that the effects of international knowledge acquisition on entrepreneurial growth will vary with firm age. Utilizing longitudinal data on 138 small and medium-sized enterprises (SMEs), we find that the acquisition of knowledge from international markets fuels growth through market development, and that this effect is stronger for international expansion than domestic expansion. Our results also show that firm age negatively moderates the relationship between international knowledge acquisition and entrepreneurial growth via the introduction of new products or services. Specifically, international knowledge acquisition has a positive effect on growth via new products/services development in young firms, but a negative effect in mature firms. We assume this reflects changes over time in how international knowledge is managed.

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Coordination of dynamic interceptive movements is predicated on cyclical relations between an individual's actions and information sources from the performance environment. To identify dynamic informational constraints, which are interwoven with individual and task constraints, coaches’ experiential knowledge provides a complementary source to support empirical understanding of performance in sport. In this study, 15 expert coaches from 3 sports (track and field, gymnastics and cricket) participated in a semi-structured interview process to identify potential informational constraints which they perceived to regulate action during run-up performance. Expert coaches’ experiential knowledge revealed multiple information sources which may constrain performance adaptations in such locomotor pointing tasks. In addition to the locomotor pointing target, coaches’ knowledge highlighted two other key informational constraints: vertical reference points located near the locomotor pointing target and a check mark located prior to the locomotor pointing target. This study highlights opportunities for broadening the understanding of perception and action coupling processes, and the identified information sources warrant further empirical investigation as potential constraints on athletic performance. Integration of experiential knowledge of expert coaches with theoretically driven empirical knowledge represents a promising avenue to drive future applied science research and pedagogical practice.

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Knowledge-based development has become a new urban policy approach for the competitive cities of the global knowledge economy era. For those cities seeking a knowledge-based development, benchmarking is an essential prerequisite for informed and strategic vision and policy making to achieve a prosperous development. Nevertheless, benchmarked knowledge-based development performance analysis of global and emerging knowledge cities is an understudied area. This paper aims to contribute to the field by introducing the methodology of a novel performance assessment model—that is the Knowledge-Based Urban Development Assessment Model—and providing lessons from the application of the model in an international knowledge city performance analysis study. The assessment model puts renowned global and emerging knowledge cities—that are Birmingham, Boston, Brisbane, Helsinki, Istanbul, Manchester, Melbourne, San Francisco, Sydney, Toronto, and Vancouver—under the knowledge-based development microscope. The results of the analysis provide internationally benchmarked snapshot of the degree of achievements in various knowledge-based urban development performance areas of the investigated knowledge cities, and reveals insightful lessons on scrutinizing the global perspectives on knowledge-based development of cities.