• 시스템엔지니어링학술지
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• 제13권2호
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• pp.49-56
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• 2017

Implementation of Model-based Systems Engineering(MBSE) depends on a model supporting efficient communication among engineers from various domains. And SysML is designed to create models supporting MBSE but unfortunately, SysML itself is not practical enough to be used in real-world engineering projects. SysML is designed to express generic systems and requires specialized knowledge, so a model written in SysML is less capable of supporting communication between a systems engineer and a sub-system engineer. Domain Specific Languages(DSL) can be a great solution to overcome the weakness of the standard SysML. A SysML based DSL means a customized SysML for a specific engineering domain. Unfortunately, current researches on SysML Domain Specific Language(DSL) for the plant engineering industry are still on the early stage. So as the first step, we have developed our own SysML based Piping & Instrumentation Diagram (P&ID) creation environment and P&ID itself of a specific plant system, using a widely used SysML authoring tool called MagicDraw. P&ID is one of the most critical output during the plant design phase, which contains all information required for the plant construction phase. So a SysML based P&ID has a great potential to enhance the communication among plant engineers of various disciplines.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.345-348
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• 2005

Because the current web search engine estimates the similarity of documents, using the frequency of words, many documents irrespective of the user query are provided. To solve these kinds of problems, the semantic web is appearing as a future web. It is possible to provide the service based on the semantic web through ontology which specifies the knowledge in a special domain and defines the concepts of knowledge and the relationships between concepts. In this paper to search the information of potential customers for home-delivery marketing, we model the specific domain for generating the ontology. And we research how to retrieve the information, using the ontology. Therefore, in this paper, we generate the ontology to define the domain about potential customers and develop the search robot which collects the information of customers.

• 한국전자거래학회지
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• 제16권2호
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• pp.143-158
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• 2011

본 연구는 Q&A(question and answer:질문-답변) 커뮤니티 사이트에서 집단지성의 특성을 추출하고, 이를 이용한 전문지식이나 정보 검색을 위한 전문영역 검색(vertical search) 을 위한 프레임워크를 제안한다, 많은 Q&A 사이트로부터 얻은 정보는 하나의 집단지성의 형태로 볼 수 있으며, 전문영역 검색은 특정 전문 분야 검색에 초점을 맞춘 검색 방법이다. 제안된 프레임워크는 사용자가 검색하고자 하는 질의어와 연관되어 있는 질문(question)과 답변(answer) 정보를 이용하여 관련어를 확장한 후, 이를 기반으로 전문지식을 요구하는 특정 도메인분야에 적용하게 된다. 이를 통해 일반 검색 엔진을 통해 검색된 검색 결과보다 유용한 정보와 전문적인 상세정보까지 제공해 줄 수 있다.

• 한국정보처리학회논문지
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• 제7권5호
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• pp.1434-1445
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• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.58-65
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• 2023

Bankruptcy is a significant risk for start-up companies, but with the help of cutting-edge artificial intelligence technology, we can now predict bankruptcy with detailed explanations. In this paper, we implemented the Category Boosting algorithm following data cleaning and editing using OpenRefine. We further explained our model using the Shapash library, incorporating domain knowledge. By leveraging the 5C's credit domain knowledge, financial analysts in banks or investors can utilize the detailed results provided by our model to enhance their decision-making processes, even without extensive knowledge about AI. This empowers investors to identify potential bankruptcy risks in their business models, enabling them to make necessary improvements or reconsider their ventures before proceeding. As a result, our model serves as a "glass-box" model, allowing end-users to understand which specific financial indicators contribute to the prediction of bankruptcy. This transparency enhances trust and provides valuable insights for decision-makers in mitigating bankruptcy risks.

• 한국정보처리학회논문지
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• 제3권7호
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• pp.1781-1791
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• 1996

전문가시스템의 지식획득, 적합한 추론기구의 설계 및 구현, 지식의 정제 등 다단계 과정으로 이뤄져 있다. 각각을 하나의 연구이슈로 다양한 연구가 진행되어 왔으나 전체를 하나로 연계해 통합적 개발에 관해서는 상대적으로 연구가 활발히 진행되지 못한 실정이다. 지식획득은 전문가에 의해 수행되는 추론과정에서 특징 응용분야의 필요한 지식이 전달되어야 하므로 시식획득과 추론을 서로 밀접한 연관성을 갖는다. 지식의 정제는 추론과정에서 일어나는 문에의 제기와 이의 해결을 통해 지식베이스의 불완전하거나 논리적 모순을 찾아 해결함으로 지식베이스를 보다 완벽하고 정확한 것으로 만드는 것이다. ㅂㄴ 연구에서는 서로 연관된 다단계 과정이 통합적으로 개발될 수 있는 환경의 설저엥 대한 하나의 방안을 제시하려한다. 특히 도메인 모델이 잘 정립되기 어려운 분야에 학습기법을 활용햇 초기 지식 베이스를 구성할 수 있는 점진적 지식획득방법과 이를 통해 만들어진 지식베이스 규칙들을 학습기법의 일종인 개념적 클러스터링 기법을 이용하여 규칙모델을 구축하고 이를 이용해 효율적인 추론이 가능하게 하며, 지식획득 과정에서는 규칙의 오류를 제시할 수 있고 이에 대한 규칙의 수정이나 새로운 규칙이 기존의 지식구조에 합당한지를 결정하는 통합적 설계방안에 대해 연구한다. 지식의 정제는 설명기구와 규칙모델을 활용하여 문제의 원인을 찾고 해결점을 제시해 그에 대한 유효성을 검증합으로 이뤄지게 한다.뤄지게 한다.

• 한국환경교육학회지:환경교육
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• 제19권3호
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• pp.80-92
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• 2006

The purpose of this study was to make valuable suggestions for improving environmental education(EE) teaching materials. For the purpose of this study, we analyzed four secondary school EE textbooks in the perspective of environmental literacy components. The findings of this study are as follows: (1) As a whole, the EE textbooks tend to focus the understanding environmental knowledge much more than environmental activities. (2) In 'main text' domain of EE textbooks, environmental information, including environmental issue knowledge, is much more focused than environmental attitudes and behavior, including socio-political and environmental issue knowledge. (3) In 'graphic data' domain, environmental information about environmental issue knowledge was most prevalent. (4) Most learning activities focus on 'issue skill' component, rather than 'attitude' and 'action' component. (5) The objectives of EE in the 7th national Curriculum were not explicitly embedded in textbooks and too much is inclined toward 'knowledge' and 'skill'. Accordingly, it is necessary to develop 'module-type' EE textbooks to enable integrative EE. Also, it is suggested to develop specific strategies for linking environmental knowledge and attitude/behavior.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.212-220
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• 2023

Ontologies are knowledge containers in which information about a specified domain can be shared and reused. An event happens within a specific time and place and in which some actors engage and show specific action features. The fact is that several ontology models are based on events called Event-Based Models, where the event is an individual entity or concept connected with other entities to describe the underlying ontology because the event can be composed of spatiotemporal extents. However, current event-based ontologies are inadequate to bridge the gap between spatiotemporal extents and participants to describe a specific domain event. This paper reviews, describes, and compares the existing event-based ontologies. The paper compares and contrasts various ways of representing the events and how they have been modelled, constructed, and integrated with the ontologies. The primary criterion for comparison is based on the events' ability to represent spatial and temporal extent and the participants in the event.

• 한국지능시스템학회논문지
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• 제8권6호
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• pp.70-77
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• 1998

Although many methods of knowledge acquisition has been developed in the exper systems field, such a need form causal knowledge acquisition hs not been stressed relatively. In this respect, this paper is aimed at suggesting a causal knowledge acquisition process, and then investigate the causal knowledge-based inference process. A vehicle for causal knowledge acquisition is FCM (Fuzzy Cognitive Map), a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain. Although FCM has a plenty of generic properties for causal knowledge acquisition, it needs some theoretical improvement for acquiring a more refined causal knowledge. In this sense, we refine fuzzy implications of FCM by proposing fuzzy causal relationship and fuzzy partially causal relationship. To test the validity of our proposed approach, we prototyped a causal knowledge-driven inference engine named CAKES and then experimented with some illustrative examples.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.173-181
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• 1997

한의학에서 환자의 병적상태를 분석하고 진단하기위한 전문가시스템은 진단과정에서 환자로부터 받아들인 지식에 기초하므로 지식은 정확하게 표현되어야 한다. 그러나 대부분의 한의진단과정에서 환자로부터 받아들인 지식은 주로 질적자료에 기초하여 기준이 애매한 개념의 지식을 많이 포함하므로 이에 대한 처리가 요구된다. 본 논문에서는 한의전문가시스템 구축에 이용되는 정보의 정확도를 높이기 위하여 Hayashi의 수량화II류를 기반으로 하여 한의진단과정에서 얻어지는 지식을 수량화하는 방법을 제안하였다.