• Title/Summary/Keyword: Domain Expert

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Retrieval methodology for similar NPP LCO cases based on domain specific NLP

  • No Kyu Seong ;Jae Hee Lee ;Jong Beom Lee;Poong Hyun Seong
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.421-431
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    • 2023
  • Nuclear power plants (NPPs) have technical specifications (Tech Specs) to ensure that the equipment and key operating parameters necessary for the safe operation of the power plant are maintained within limiting conditions for operation (LCO) determined by a safety analysis. The LCO of Tech Specs that identify the lowest functional capability of equipment required for safe operation for a facility must be complied for the safe operation of NPP. There have been previous studies to aid in compliance with LCO relevant to rule-based expert systems; however, there is an obvious limit to expert systems for implementing the rules for many situations related to LCO. Therefore, in this study, we present a retrieval methodology for similar LCO cases in determining whether LCO is met or not met. To reflect the natural language processing of NPP features, a domain dictionary was built, and the optimal term frequency-inverse document frequency variant was selected. The retrieval performance was improved by adding a Boolean retrieval model based on terms related to the LCO in addition to the vector space model. The developed domain dictionary and retrieval methodology are expected to be exceedingly useful in determining whether LCO is met.

An Investigation of a Way of Career Education: How is the Dream of the Best Field Experts Achieved? (진로 교육 방안 모색: 분야 최고 전문가의 꿈은 어떻게 이루어지는가?)

  • Song, Kwang-Han
    • Journal of the Korea Convergence Society
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    • v.9 no.1
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    • pp.405-418
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    • 2018
  • This paper was carried out to provide basic data for career search of the free school system. Putting the goal of career education into cultivating expertise, the review was made on the results of the previous studies on the requirements of professional practice. However, As the controversy over the requirements of professional practice has not been solved, so the core elements related to expert performance were examined as a whole through a fundamental cognitive mechanism from which diverse human cognitive characteristics appear. The results show that expert domains consists of content and representation that can exist in an integrated to a great variety of combinations between the two or independent manner, and each domain or field expert performance require different levels of the elements such as intelligence, internal thinking, curiosity (motivation), and obsession (task commitment); and the birth of 1% experts in a domain or field is determined by the obsession. Based on the results, this paper discusses issues related to professionalism and provides a concrete approach to career search during the free semester.

Development of Expert Systems using Automatic Knowledge Acquisition and Composite Knowledge Expression Mechanism

  • Kim, Jin-Sung
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.447-450
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    • 2003
  • In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

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A Tool for Implementation of Expert System with Knowledge Management System (지식관리 시스템을 수반한 전문가 시스템 구축 도구)

  • 서의현
    • Journal of Intelligence and Information Systems
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    • v.9 no.3
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    • pp.49-63
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    • 2003
  • This paper proposes and implements a tool for the development of efficient and reliable expert system. In the expert system the inference is executed, based on the knowledges stored in the knowledge base of specific domain. To acquire the reliable results of inference, the expert system requires the facilities which can access the various kinds of knowledge and maintain the consistency and accuracy of knowledge. In this context this paper implemented the knowledge management system which maintains the consistency and accuracy of knowledge, adding selectively the knowledges without error to the knowledge base by verifying their error before the knowledges are added to the knowledge base. At the same time this paper made the expert system call and use the procedural knowledge and the declarative knowledge in the data base so that it might use the various kinds of knowledge in the process of inference.

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General problem solver를 이용한 intelligent LP 모형화에 대한 연구

  • 박성주;권오병
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1991.10a
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    • pp.469-474
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    • 1991
  • Recent interests in intelligent LP modeling aim to support MS/OR-naive users to be able to apply LP models to practical problems without the expert knowledges required. For more generalized LP modeling, a GPS(General Problem Solver)-based approach is suggested in this paper. It identifies modeling process as a means-ends analysis process. In view of this approach, a) we first divide the knowledges into domain specific assertive knowledges(state) and procedural knowledges about LP modeling(operator and macro) for model-domain independence, b) and then generate LP model according to the difference resolution techniques.

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A study on the quantification for Oriental Medicine Data (한의학자료의 수량화에 대한 연구)

  • Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
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    • v.8 no.2
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    • pp.173-181
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    • 1997
  • In oriental medicine, it is required that correct medical knowledge should be maintained for medical expert system which analyzes and diagnoses patients symptoms. Typical medical expert system has a knowledge base as its core, and the knowledge base contains a domain specific knowledge about patients records. However, oriental medicine diagnostic knowledge is formed mostly as qualitative data, knowledge could be ambiguous and uncertain. In this paper, we looked at quantification methods and propose a method for quantifying the oriental medicine diagnostic knowledge, which is improving the knowledge base of an oriental medicine expert system.

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Development of The Expert System for Repair of Cracks on R/C Structures (철근 콘크리트 구조물에 발생한 균열보수를 위한 전문가시스템 개발)

  • 심종성;심재원
    • Proceedings of the Korea Concrete Institute Conference
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    • 1993.10a
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    • pp.71-78
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    • 1993
  • The R/C structures is very popular because of its low construction cost and its semi-permanent life. But in Korea, unfortunately there are few exprets in this field, and the repair methods and selection of material for R/C structures are determined by their subjective personal opinions. Therefore systematic study of this field is ulgently required. For attainning this purpose, in this study the related documents and knowledge or experience from human experts were collected. Based on the collected information cracks are classified into 25 patterns and repair related-knowledge base, which will be formulated and encoded into the domain knowledge, is built. And then an expert system, that can suggest the repair methods in the same way the human experts would, is developed. The results using the developed expert system are compared to the real field practices and they are satisfactory.

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An Expert System of Moulding Working for Air Intake Hose Products using 3-Dimensional Parametric Modeling Technique

  • Sang Bong Park
    • Korean Journal of Computational Design and Engineering
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    • v.3 no.3
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    • pp.168-176
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    • 1998
  • This paper deals with an application on the mould machining of air intake hose product by using 3-dimensional parametric modeling techniques. The detailed domain is the 3-dimensional product with similar shapes and different sizes which needs too much working time for preparation of modeling or machining due to making a trial and errors repeatedly. Decision making rules for selection of modeling order and technique, and for calculation of cutting conditions, and for determination of sequence and method concerning machining operations are required by interview of expert engineers in the field. The developed expert system of modeling and machining is programmed by using a user programming language under the CAD/CAM software of the Personal Designer. The developed system that aids a mould engineer who is working in the modeling and machining section which deal with air intake hose product provides strong and useful capabilities.

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Integrating Case-Based Reasoning with DSS (DSS와 사례기반 추론의 결합)

  • Kim Jin-Baek
    • Management & Information Systems Review
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    • v.2
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    • pp.169-193
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    • 1998
  • Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

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Ontology-based Knowledge Framework for Product Development (제품개발을 위한 온톨로지 기반 지식 프레임워크)

  • Suh H.W.;Lee J.H.
    • Korean Journal of Computational Design and Engineering
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    • v.11 no.2
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    • pp.88-96
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    • 2006
  • This paper introduces an approach to ontology-based framework for knowledge management in a product development domain. The participants in a product life cycle want to share the product knowledge without any heterogeneity. However, previous knowledge management systems do not have any conceptual specifications of their knowledge. We suggest the three levels of knowledge framework. First level is an axiom, which specifies the semantics of concepts and relations. Second level is a product development knowledge map. It defines the common domain knowledge which domain experts agree with. Third level is a specialized knowledge for domain, which includes three knowledge types; expert knowledge, engineering function and data-analysis-based knowledge. We propose an ontology-based knowledge framework based on the three levels of knowledge. The framework has a uniform representation; first order logic to increase integrity of the framework. We implement the framework using prolog and test example queries to show the effectiveness of the framework.