• Title/Summary/Keyword: ELECTRA

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A Systematic Study on the Bryozoas from the South Sea in Korea I. Cheilostomata (한국 남해산 태충류의 계통분류학적 연구 I. 순구류)

  • 서지은
    • Animal Systematics, Evolution and Diversity
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    • v.8 no.1
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    • pp.141-160
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    • 1992
  • The systematic study on the bryozoans from the South SEa in Korea was done with the materials collected at 49 localities from 1965 to 1991. As a result, 57 species in two suborders of cheilostomaous bryozoans were identified, which seven species, Electra tenella, Labioporella bursaria, Dendrobeania longispinosa, Sinupetraliella gigantea, Cryptosula pallasiana, Hippopodina feegeensis and Durystomella bilabiata were new to Korean fauna. The unrecorded species and the species which need remarking were described with plates.

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Examining Suicide Tendency Social Media Texts by Deep Learning and Topic Modeling Techniques (딥러닝 및 토픽모델링 기법을 활용한 소셜 미디어의 자살 경향 문헌 판별 및 분석)

  • Ko, Young Soo;Lee, Ju Hee;Song, Min
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.32 no.3
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    • pp.247-264
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    • 2021
  • This study aims to create a deep learning-based classification model to classify suicide tendency by suicide corpus constructed for the present study. Also, to analyze suicide factors, the study classified suicide tendency corpus into detailed topics by using topic modeling, an analysis technique that automatically extracts topics. For this purpose, 2,011 documents of the suicide-related corpus collected from social media naver knowledge iN were directly annotated into suicide-tendency documents or non-suicide-tendency documents based on suicide prevention education manual issued by the Central Suicide Prevention Center, and we also conducted the deep learning model(LSTM, BERT, ELECTRA) performance evaluation based on the classification model, using annotated corpus data. In addition, one of the topic modeling techniques, LDA identified suicide factors by classifying thematic literature, and co-word analysis and visualization were conducted to analyze the factors in-depth.

Re-defining Named Entity Type for Personal Information De-identification and A Generation method of Training Data (개인정보 비식별화를 위한 개체명 유형 재정의와 학습데이터 생성 방법)

  • Choi, Jae-hoon;Cho, Sang-hyun;Kim, Min-ho;Kwon, Hyuk-chul
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.206-208
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    • 2022
  • As the big data industry has recently developed significantly, interest in privacy violations caused by personal information leakage has increased. There have been attempts to automate this through named entity recognition in natural language processing. In this paper, named entity recognition data is constructed semi-automatically by identifying sentences with de-identification information from de-identification information in Korean Wikipedia. This can reduce the cost of learning about information that is not subject to de-identification compared to using general named entity recognition data. In addition, it has the advantage of minimizing additional systems based on rules and statistics to classify de-identification information in the output. The named entity recognition data proposed in this paper is classified into twelve categories. There are included de-identification information, such as medical records and family relationships. In the experiment using the generated dataset, KoELECTRA showed performance of 0.87796 and RoBERTa of 0.88.

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Verification of educational goal of reading area in Korean SAT through natural language processing techniques (대학수학능력시험 독서 영역의 교육 목표를 위한 자연어처리 기법을 통한 검증)

  • Lee, Soomin;Kim, Gyeongmin;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.13 no.1
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    • pp.81-88
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    • 2022
  • The major educational goal of reading part, which occupies important portion in Korean language in Korean SAT, is to evaluated whether a given text can be fully understood. Therefore given questions in the exam must be able to solely solvable by given text. In this paper we developed a datatset based on Korean SAT's reading part in order to evaluate whether a deep learning language model can classify if the given question is true or false, which is a binary classification task in NLP. In result, by applying language model solely according to the passages in the dataset, we were able to acquire better performance than 59.2% in F1 score for human performance in most of language models, that KoELECTRA scored 62.49% in our experiment. Also we proved that structural limit of language models can be eased by adjusting data preprocess.

Analyzing Effective Poll Prediction Model Using Social Media (SNS) Data Augmentation (소셜 미디어(SNS) 데이터 증강을 활용한 효과적인 여론조사 예측 모델 분석)

  • Hwang, Sunik;Oh, Hayoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.12
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    • pp.1800-1808
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    • 2022
  • During the election period, many polling agencies survey and distribute the approval ratings for each candidate. In the past, public opinion was expressed through the Internet, mobile SNS, or community, although in the past, people had no choice but to survey the approval rating by relying on opinion polls. Therefore, if the public opinion expressed on the Internet is understood through natural language analysis, it is possible to determine the candidate's approval rate as accurately as the result of the opinion poll. Therefore, this paper proposes a method of inferring the approval rate of candidates during the election period by synthesizing the political comments of users through internet community posting data. In order to analyze the approval rate in the post, I would like to suggest a method for generating the model that has the highest correlation with the actual opinion poll by using the KoBert, KcBert, and KoELECTRA models.

Zero-shot Korean Sentiment Analysis with Large Language Models: Comparison with Pre-trained Language Models

  • Soon-Chan Kwon;Dong-Hee Lee;Beak-Cheol Jang
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.2
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    • pp.43-50
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    • 2024
  • This paper evaluates the Korean sentiment analysis performance of large language models like GPT-3.5 and GPT-4 using a zero-shot approach facilitated by the ChatGPT API, comparing them to pre-trained Korean models such as KoBERT. Through experiments utilizing various Korean sentiment analysis datasets in fields like movies, gaming, and shopping, the efficiency of these models is validated. The results reveal that the LMKor-ELECTRA model displayed the highest performance based on F1-score, while GPT-4 particularly achieved high accuracy and F1-scores in movie and shopping datasets. This indicates that large language models can perform effectively in Korean sentiment analysis without prior training on specific datasets, suggesting their potential in zero-shot learning. However, relatively lower performance in some datasets highlights the limitations of the zero-shot based methodology. This study explores the feasibility of using large language models for Korean sentiment analysis, providing significant implications for future research in this area.

Architecture Design of Fault Tolerant Digital Library Service (장애 감내형 디지털도서관 서비스 구조 설계)

  • Kim, Ki-Young;Sul, Dong-Myoung;Choi, Hoon
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.436-438
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    • 1998
  • 신뢰성 향상은 분산 시스템의 기본 목표이며, 이를 위하여 서비스를 제공해 주는 서버 객체의 중복이 불가피 하다. 본 논문에서는 중복과 함께 고려되어야 할 기본적인 사항들을 알아보고, 현재의 시스템들을 CORBA 환경과 CORBA 에 기반하지 않은 환경으로 나누어, 각각의 시스템 환경하에서 신뢰성 있는 분산 어플리케이션의 구현을 제공하기 위해 진행되었던 연구 사례로 Orbix+Isis, Electra와 Chameleon을 소개한다. 또한 디지털 도서관에서 핸들 서비스를 제공하고 있는 핸들 서버의 장애 감내을 위한 장애 감내형 다중화 서버 모델을 제시하고, 이를 제공하기 위한 ILU의 인터페이스를 제시함으로써, 장애 감내형 디지털 도서관 서비스 구조 설계에 관한 연구를 소개한다.

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Puritan Values as 'Force Behind' in Mourning Becomes Electra

  • Yang, Seung-Joo
    • English Language & Literature Teaching
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    • v.11 no.4
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    • pp.79-96
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    • 2005
  • Eugene O'Neill portrays Puritan values of the Mannon family inherited from their family past. Since Puritan values of the Mannons suppress the normal way of life and love, they retain only rigidity, without the charity which is the core element of the teaching of Christianity. With Puritan repression and its dissociation from the vital spring of life, the Puritan Mannons live in a world drained of life and in a world of hypocrisy between outer beauty and inner ugliness. Ironically, they think more of death itself, neglecting to feel the vitality of life. Working as a fate, Puritan values of the Mannon as 'Force Behind' in O'Neill's own term are the cause of suffering and destruction of the Mannons throughout the whole play. The mask-like house and faces are effectively used as a dramatic technique to express the distorted Puritan values.

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Reliability Test for the Repairing Joint in HVDC Sea Submarine Cable (HVDC 해저케이블 접속재 신뢰성 평가를 위한 인정시험)

  • Yang, B.M.;Park, H.S.;Park, J.W.;Kim, J.C.;Kang, J.W.;Yoon, H.H.
    • Proceedings of the KIEE Conference
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    • 2008.10a
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    • pp.77-78
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    • 2008
  • HVDC 케이블은 장거리 전력전송, 국가간 계통연계 비동기 전력계통연계, 전력의 시장화에 따른 전력공급 제어 필요에 따라 세계적으로 널리 사용되고 있다. 국내에서는 현재 유일하게 제주-해남간 HVDC 해저케이블이 운영 중에 있으며, 향후 제주도 안정적인 전력공급을 위하여 2011년에 제주-육지간 HVDC 해저케이블이 추가로 건설될 예정이다. 그래서 HVDC 해저 케이블의 안정적이고 신뢰성 있는 운영을 하기 위한 보수자재용 접속재 개발 및 신뢰성 평가가 필요하게 되었다. 본 논문에서는 제주-해남간 운영중인 HVDC 해저케이블 보수자재용으로 개발된 접속재에 대한 신뢰성 평가 방법으로 가장 많이 사용되고 있는 Electra 175, 189의 기계적 및 전기적 평가에 대하여 기술하고자 한다.

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The Standard Comparison of Calculating the Permissible Current Carrying Capability for Overhead Transmission Line (가공송전선로의 허용전류 계산 규격의 검토)

  • Jeong, S.H.;Nam, K.Y.;Lee, J.D.;Choi, S.B.;Ryoo, H.S.
    • Proceedings of the KIEE Conference
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    • 2006.07a
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    • pp.274-275
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    • 2006
  • The IEEE std 738 and Cigre Electra documents are well known as the standard of calculating the ampacity of overhead conductors. Although these two standards use the same basic heat balance concept, they use different applicable methods to calculate ampacity ratings. This paper examines the concept of basic heat balance equation and the differences of each term of basic heat balance equation.

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