• 한국CDE학회논문집
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• 제4권1호
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• pp.52-59
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• 1999

The CAD/CAM System for deep drawing transfer die tin mechanical press process has been developed. The developed CAD system can generate the drawing of transfer die in mechanical press. Using thee results from CAD system, it can generate the NC data to machine die's elements on the CAD system. This system can reduce design man-hour an human errors. In order to construct the system, it is used to automated the design process and generate the NC data using concepts of the designing rule and the machining rule. The developed system is based on the knowledge base system which is involved a lot of expert's technology in the practice field. Using AutoLISP language under the AutoCAD system, CTK customer language of SmartCAM is used as the overall CAD/CAM environment. Results of this system will be provide effective aids to the designer and manufacturer in this field.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.307-310
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• 1995

In the conventional systems, a human must have knowledge of machines and of their special language in communicating with machines. In one side, it is desirable for a human but in another side, it is true that achieving it is very elaborate and is also a significant cause of human error. To reduce this sort of human load, an intelligent man-machine interface is desirable to exist between a human operator and machines to be operated. In the ordinary human communication, not only linguistic information but also visual information is effective, compensating for each others defect. From this viewpoint, problem of translating verbal expressions to some visual image is discussed here in this paper. The location relation between any two objects in a visual scene is a key in translating verbal information to visual information, as is the case in Fig.l. The present translation system advances in knowledge with experience. It consists of Japanese Language processing, image processing, and Japanese-scene translation functions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.194-199
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• 2003

Data are an expression of the language or numerical values that show some features. And the information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns or make a decision. Today, knowledge extraction and application of that are broadly accomplished for the easy comprehension and the performance improvement of systems in the several industrial fields. The knowledge extraction can be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge is drawn by rules with data mining techniques. Clustering (CL), input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for the knowledge expression based upon rules. In this paper, the various approaches of the knowledge extraction are surveyed and categorized by methodologies and applied industrial fields. Also, the trend and examples of each approaches are shown in the tables and graphes using the categories such as CL, ISP, NF, NN, EM, and so on.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1307-1312
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• 2004

Word sense disambiguation is one of the most important problems in natural language processing research topics such as information retrieval and machine translation. Many approaches can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledge-based, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy. The purpose of this paper is to compare three famous machine learning techniques, Snow, SVM and Naive Bayes in Word-Sense Disambiguation on Thai language. 10 ambiguous words are selected to test with word and POS features. The results show that SVM algorithm gives the best results in solving of Thai WSD and the accuracy rate is approximately 83-96%.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1253-1256
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• 2003

These days, companies have to process enormous information and knowledge to satisfy desire of customers. The mere storage of them is no longer a significant problem because of the immense progress information technology has made during the past years and decades. It is important to deliver the right piece of information to the right person at the right time. Consequently, Knowledge management which supports the exchange of relevant information within company organization structure is of special interest for current enterprises. To solve this problem, a concept of the Knowledge management system is introduced in this paper based on the ontology technology. An ontology can describe all relevant information about documents, products, organizational structures or the users, their interests and experiences and be understood by everybody.

• 한국정밀공학회지
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• 제15권5호
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• pp.50-58
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• 1998

A proper model of expert system for the very thin sheet metal press die design has been suggested. Using the suggested model, an expert system of the very thin sheet metal press die has been developed. This study contains that the results from the developed system for three kinds of specimens have the adaptability in the actual site. In addition, the possibility for expansion of this system has been discussed. The developed system, which is based on the knowledge base, has been included in a lot of expert's technology in the practice field. C-language under the HP-UNIX system and CIS customer language of the EXCESS CAD/CAM system have been used as the overall CAD environment. Results from this system will provide effective aids to the designer in this field.

• ETRI Journal
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• 제42권2호
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• pp.239-246
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• 2020

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.

• 한국한의학연구원논문집
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• 제12권1호
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• pp.1-12
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• 2006

Recently according to the WIPO's policy of preserving traditional knowledge, constructing the database of traditional knowledge is in progress. To maximize the retrieving power of the knowledge resource systems which will be developed later, it is necessary to construct the ontology for the concepts used by traditional knowledge. In order to construct the ontology systematically, a standardized ontology representation method is needed, and OWL(Web Ontology Language) is the recommendation of W3C(World Wide Web Consortium) and is widely used. Ontology tools can be used to ease the construction of OWL ontology, but no research about the comparison of OWL ontology tools exists. This paper compares the tools of OWL by an objective point of view and with that one can make a decision of using the appropriate tool for constructing OWL ontologies.

• Korean Journal of Radiology
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• 제25권2호
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• pp.126-133
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• 2024

Large language models (LLMs) have revolutionized the global landscape of technology beyond natural language processing. Owing to their extensive pre-training on vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without additional fine-tuning. General-purpose chatbots based on LLMs can optimize the efficiency of radiologists in terms of their professional work and research endeavors. Importantly, these LLMs are on a trajectory of rapid evolution, wherein challenges such as "hallucination," high training cost, and efficiency issues are addressed, along with the inclusion of multimodal inputs. In this review, we aim to offer conceptual knowledge and actionable guidance to radiologists interested in utilizing LLMs through a succinct overview of the topic and a summary of radiology-specific aspects, from the beginning to potential future directions.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2006년도 제18회 한글 및 한국어 정보처리 학술대회
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• pp.15-21
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• 2006

본 논문에서는 올바른 한국어 생활과 한국어 실력 향상을 위하여, 한국어 어휘에 대한 풍부한 정보를 담고 있는 한국어사전, 사용자 어휘지능망(User-Word Intelligent Network : U-WIN)등의 언어자원을 이용한 자동문제생성기술을 소개하고, 이를 이용한 한국어 어휘학습시스템을 제시한다. 대부분의 학습시스템에서 사용하는 문제 은행식 출제 방식의 문제점을 해소할 수 있는 하나의 방법으로서, 기존의 한국어 어휘문제의 문항을 분석하여 8가지 문제 유형으로 재편성하고, 각 유형별 자동 문제 생성패턴에 따라 언어자원이 가지고 있는 한국어 어휘의 형태적 정보, 의미적 정보를 이용하여 한국어 어휘 문제를 자동 출제하는 한국어 어휘학습시스템을 구현하였다.