• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.7-14
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• 2000

본 글은 1999년 5월 CASA/SME Blue Book에 Jim Jordan 그리고 Fred Michel이 “Next Generation Manufacturing”라는 제목으로 게재한 자료를 편자의 의도에 따라 재편집한 것입니다. CASA(Computer and Automated Systems Association)는 SME(Society of Manufacturing Engineers)에서 활동하고 있는 하나의 분과로서 CIM Enterprise Wheel을 만들어 내 유명한 곳이기도 합니다. 저자는 본 괌에서 앞으로 10여 년 간 펼쳐질 차세대 제조 시스템에서는 지식의 경영이 가장 중요한 요소라고 정의하고 있습니다. 그리고 차세대 제조 시스템의 운영전략으로는 기업통합, 인간자원의 지적이용, 지식의 개발 및 유지, NGM 프로세스 장비 및 기술의 채용을 들고 있습니다. 차세대 제조 시스템(1)은 전월호에서 소재되었습니다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1744-1751
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• 2008

This paper presents a monitor positioning algorithm to identify the power quality event source in the distribution system with distributed generations. This algorithm determines the appropriate number of monitors and their locations considering power system topology together with distributed generation. This paper summarizes the guidelines of monitor positioning into five principles and defines the weighting factors according to the principles. To evaluate the adequacy of monitor positioning results, ambiguity indices considering monitor location and system topology are proposed. The optimal number and locations of monitors are determined from optimization routine using the weighting factors and the monitor positioning results are evaluated in terms of ambiguity indices. The algorithm is applied to IEEE 13 bus test feeder and suggests the optimal number and locations of power quality monitors. The proposed approach can realize the expert's knowledge on monitor positioning into a sophisticated automatic computing algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.58-63
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• 2006

This paper describes a novel automated analysis system for bellows of piping system. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy theory and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes and one of commercial solid modelers. In this system, a geometric model, i.e. an analysis model, is first defined using a commercial solid modelers for 3-D shell structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation technique is introduced as a basic tool for element generation. The triangular elements are converted to quadrilateral elements. Practical performances of the present system are demonstrated through several analysis for bellows of piping system.

• Korean Journal of Child Studies
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• v.31 no.6
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• pp.15-34
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• 2010

The present study examines the sex differences in 5-year-old preschoolers' aggression according to the type of aggression (overt, relational) and the effect of components of social information processing (SIP : interpretation, goal clarification, response generation, response evaluation) and emotional factors (emotionality, emotional knowledge, emotion regulation) on their aggression. The subjects were 112 5-year-olds (56 boys, 56 girls) and their 11 teachers recruited from 9 day-care centers in Seoul and Kyung-Ki province. Each child's SIP and emotional knowledge were individually assessed with pictorial tasks and teachers reported on children's aggression, emotionality, and emotion regulation by questionnaires. Results indicated that there was a significant sex difference only in the preschoolers' overt aggression. Overtly aggressive response generation in SIP was the strongest predictor of preschoolers' overt aggression while anger of negative emotionality in emotional factors was the strongest predictor of preschoolers' relational aggression.

• Journal of Digital Convergence
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• v.14 no.3
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• pp.251-260
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• 2016

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patent, and project reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer the further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a RDB-to-Triples transformer is implemented. Lastly, we show an experiment on R&D data integration using the lightweight ontology, triples generation, and visualization and navigation of the knowledge map.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.27-38
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• 2023

In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.

• Journal of the Korean earth science society
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• v.28 no.6
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• pp.673-685
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• 2007

The purpose of this study was to investigate Earth Systems Understandings (Mayer, 1991) and Earth Systems meaning generation reported by science-talented students who participated in a geological field trip. The eight (4 female and 4 male students) field trip reports were randomly selected among all the reports written by twenty eighth-grade students who joined Shiwha-Lake field trip in Korea. The three-step program, including preparation, field trip, and summary, was provided to the students in order to facilitate meaningful learning through outdoor teaming activities. Seven Earth Systems Understandings and thematic types (Keys, 1999) were used to analyze the reports. The results of this study indicated thai aesthetic views and stewardship toward the Earth, which were the most distinguishing characteristics in Earth Systems Education, were reflected on most of the reports. The results also showed that the students tried to represent their understandings in such a type as meaning extension, meaning enhancement, or meaning elaboration. Overall, many students used 'knowledge-telling' process with a long list of observations and facts, whereas a few students used higher-order 'knowledge-transforming' process by coordinating their findings with interpretations and reasoning in their writings.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.42-52
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• 2002

Information extraction(IE) is a process of recognizing and fetching particular information fragments from a document. In previous work, most IE systems generate the extraction rules called the wrappers manually, and although this manual wrapper generation may achieve more correct extraction, it reveals some problems in flexibility, extensibility, and efficiency. Some other researches that employ automatic ways of generating wrappers are also experiencing difficulties in acquiring and representing useful domain knowledge and in coping with the structural heterogeneity among different information sources, and as a result, the real-world information sources with complex document structures could not be correctly analyzed. In order to resolve these problems, this paper presents an agent-based information extraction system named XTROS that exploits the domain knowledge to learn from documents in a semi-structured information source. This system generates a wrapper for each information source automatically and performs information extraction and information integration by applying this wrapper to the corresponding source. In XTROS, both the domain knowledge and the wrapper are represented as XML-type documents. The wrapper generation algorithm first recognizes the meaning of each logical line of a sample document by using the domain knowledge, and then finds the most frequent pattern from the sequence of semantic representations of the logical lines. Eventually, the location and the structure of this pattern represented by an XML document becomes the wrapper. By testing XTROS on several real-estate information sites, we claim that it creates the correct wrappers for most Web sources and consequently facilitates effective information extraction and integration for heterogeneous and complex information sources.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.942-950
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• 1998

Extraction of knowledge, especially in the form of rules, from raw data is very important in data mining, the aim of which is to help users who feel the lack of knowledge in spite of the abundance of data. Logic minimization tools are ones which derive optimized knowledge given ON set and DC set. First, the parallel expansion scheme of logic minimization is extracted and used to obtain intial knowledge to get final rules, which are successfully applicable to real world data. The prototype system based on this new approach has been experimented with real world data to show that it is as practical as conventional long studied decision tree methods like C4.5 system.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11b
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• pp.1297-1300
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• 2003

본 논문은 웹 온톨로지 데이터를 접근, 표현 및 처리 할 수 있는 온톨로지 객체 모델을 생성하기 위한 시스템이다. 시멘틱 웹의 대두로 인해 웹 상에 존재하는 데이터의 특성에 따라서 접근 할수 있는 방법도 다양화 되었다. 이에 웹 상에서 산재되어 있는 지식들을 가져와 각 도메인에 맞게 새로운 온톨로지를 생성하고 서로 다른 언어로 표현된 온톨로지를 계층 어휘들을 이용하여 시멘틱웹 환경에서 지식을 처리하기 위해 웹 온톨로지를 구축하고 처리할 수 있는 온톨로지 객체 모델을 제공하고, 온톨로지 객체 모델 API를 통해 외부 어플리케이션과의 정보를 교환한다. 본 논문에서는 웹 온톨로지를 표현하기 위한 모델을 계층별로 구별하여 프레임 기반의 상위 온톨로지(frame-based ontology layer), 다른 도메인에서도 사용이 가능한 공통된 어휘(vocabulary)를 표현한 핵심 온톨로지(generic ontology layer)와 각각의 온톨로지 언어에 의존적인 어휘를 표현한 기능 온톨로지(functional ontology layer)로 구성하여 표현의 중복을 없애고 재 사용성을 높이기 위한 모델을 제공함으로써, 온톨로지 추론, 병합 및 저작 도구 등의 외부 어플리케이션이 온톨로지 객체 모델에 손쉽게 접근할수 있고, 온톨로지에 대한 쉬운 지식 표현 및 핸들링을 제공할 수 있다.