• 대한전기학회논문지
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• 제43권5호
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• pp.809-818
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• 1994

In this paper , the author proposed FLVSC (Fuzzy Logic Variable Structure Controller),of which control rules are extracted from the concepts of VSC(Variable Structure Control). FLC(Fuzzy Logic Controller) based on linguistic rules has the advantages of not needing of some exact mathematical model for plant to be controlled. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbances, parameter variations and uncertainties in sliding mode. In addition, the method has the properties of FLC-noise rejection capability etc. The computer simulations have been carried out for position control of DC servo motor to show the usefulness of the proposed method and the effects of disturbances and parameter variations are considered.

• 전기학회논문지
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• 제66권12호
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• pp.1751-1758
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• 2017

This paper presents a fuzzy logic system with data preprocessing to make the accurate electric power load prediction system. The fuzzy logic system acceptably treats the hidden characteristic of the nonlinear data. The data preprocessing processes the original data to provide more information of its characteristics. Thus the combination of two methods can predict the given data more accurately. The former uses TSK fuzzy logic system to apply the linguistic rule base and the linear regression model while the latter uses the linear interpolation method. Finally, four regional electric power load data in taiwan are used to evaluate the performance of the proposed prediction system.

• 한국구조물진단유지관리공학회 논문집
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• 제2권2호
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• pp.151-161
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• 1998

In this study, an attempt is made to apply the concept of fuzzy-bayesian theory to the integrity assessment of RC highway bridge, and uncertainty states are represented in terms of fuzzy sets which define several linguistic variables such as "very good", "good", "average", "poor", "very poor", etc. Especially, the concept of fuzzy conditional probability aids to derive a new reliability analysis which includes the subjective assessment of engineers without introducing any additional correction factors. The fuzzy concept are also used as reliability indexes for the condition assessment based on the proposed models, the proposed fuzzy theory-based approach with the results of visual inspection and extensive field load tests are applied to the integrity assessment of a new RC highway bridge, namely, Jichok bridge.

• 한국구조물진단유지관리공학회 논문집
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• 제3권2호
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• pp.233-240
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• 1999

Even though the recent construction safety disasters not only result in the loss inside construction sites but also become to a large public disasters, safety activities are managed in an irrational way and safety rules are ignored in the construction sites which leads to occur same type of disasters repeatedly. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the general construction projects safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique base on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

• Genomics & Informatics
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• 제17권2호
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• pp.19.1-19.10
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• 2019

In this paper, we investigate cross-platform interoperability for natural language processing (NLP) and, in particular, annotation of textual resources, with an eye toward identifying the design elements of annotation models and processes that are particularly problematic for, or amenable to, enabling seamless communication across different platforms. The study is conducted in the context of a specific annotation methodology, namely machine-assisted interactive annotation (also known as human-in-the-loop annotation). This methodology requires the ability to freely combine resources from different document repositories, access a wide array of NLP tools that automatically annotate corpora for various linguistic phenomena, and use a sophisticated annotation editor that enables interactive manual annotation coupled with on-the-fly machine learning. We consider three independently developed platforms, each of which utilizes a different model for representing annotations over text, and each of which performs a different role in the process.

• 말소리와 음성과학
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• 제14권4호
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• pp.19-24
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• 2022

This study examined which acoustic cue(s) that Korean learners of English give weight to in perceiving English lexical stress. We manipulated segmental and suprasegmental cues in 5 steps in the first and second syllables of an English stress minimal pair "object". A total of 27 subjects (14 native speakers of English and 13 Korean L2 learners) participated in the English stress judgment task. The results revealed that native Korean listeners used the F0 and intensity cues in identifying English stress and weighted vowel quality most strongly, as native English listeners did. These results indicate that Korean learners' experience with these cues in L1 prosody can help them attend to these cues in their L2 perception. However, L2 learners' perceptual attention is not entirely predicted by their linguistic experience with specific acoustic cues in their native language.

• 한국정밀공학회지
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• 제12권4호
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• pp.28-38
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• 1995

The flank wear at the minor cutting edge significantly affects the geometric accuracy and surface roughness in finish machining. A fuzzy estimator based on a fuzzy inference algorithm with a max-min composition rule is introduced to evaluate the minor flank wear length. The features sensitive to minor flank wear are extracted from the dispersion analysis of a time series AR model of the feed directional acceleration signal. These features, dispersions, are used for constructing linguistic rules, and then the fuzzy inferences are carried out with test data sets collected under various cutting conditions. The proposed system turns out to be effective for estimating minor flank wear length.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2019년도 제31회 한글 및 한국어 정보처리 학술대회
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• pp.149-152
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• 2019

감성분석이란 입력된 텍스트의 감성을 분류하는 자연어처리의 한 분야로, 최근 CNN, RNN, Transformer등의 딥러닝 기법을 적용한 다양한 연구가 있다. 한국어 감성분석을 진행하기 위해서는 형태소, 음절 등의 추가 자질을 활용하는 것이 효과적이며 성능 향상을 기대할 수 있는 방법이다. 모델 생성에 있어서 아키텍쳐 구성도 중요하지만 문맥에 따른 언어를 컴퓨터가 표현할 수 있는 지식 표현 체계 구성도 상당히 중요하다. 이러한 맥락에서 BERT모델은 문맥을 완전한 양방향으로 이해할 수있는 Language Representation 기반 모델이다. 본 논문에서는 최근 CNN, RNN이 융합된 모델과 Transformer 기반의 한국어 KoBERT 모델에 대해 감성분석 task에서 다양한 성능비교를 진행했다. 성능분석 결과 어절단위 한국어 KoBERT모델에서 90.50%의 성능을 보여주었다.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.85-91
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• 2024

Currently, generative artificial intelligence is a hot topic around the world. Generative artificial intelligence creates various images, art, video clips, advertisements, etc. The problem is that it is very difficult to verify the internal work of artificial intelligence. As a requirements engineer, I attempt to create a toon image by applying linguistic mechanisms to the current issue. This is combined with the UML object model through the semantic role analysis technique of linguists Chomsky and Fillmore. Then, the derived properties are linked to the toon creation template. This is to ensure productivity based on reusability rather than creativity in toon engineering. In the future, we plan to increase toon image productivity by incorporating software development processes and reusability.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권12호
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• pp.1649-1659
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• 2004

텍스트 생성(text generation)은 언어가 아닌 다양한 지식원으로부터 텍스트를 생성해 내는 언어 처리의 한 분야로, 여러 가지 복합적이고 단계적인 과정을 통해 이루어진다. 본 논문에서는 자연스러운 텍스트 생성을 위한 여러 과정 중, 한번 언급된 대상(entity)을 자연스럽게 지시(refer)하기 위한 지시어 생성(referring expression generation), 특히 한국어에 두드러진 영형(zero pronoun)에 의한 대용화(pronominalization) 과정에 초점을 맞춘다. 이를 위해, 구문 정보와 비용기반 중심화 이론(cost-based centering model)을 바탕으로, 한국어에 적합한 지시어 특히 영형의 생성에 영향을 미치는 다양한 자질(feature)들온 규명하고, 기계 학습을 통해 지시어 생성 모델을 구축하였다. 세 개의 장르 - 묘사문(설명문), 뉴스, 짧은 우화 - 에서 총 95개의 텍스트로부터 학습이 이루어 졌으며 이론 대상으로, 제안된 자질들이 지시어의 생성, 특히 영형의 생성에 효율적으로 적용될 수 있음을 보였다. 또한, 지시어 생성과 관련된 기존의 방법론들과 본 논문에서 제안한 모델을 비교하여 성능이 크게 향상되었음을 보이고, T-test를 통해 99.9%의 신뢰 구간에서 그 성능 향상이 통계적으로 의미가 있음을 확인하였다.