• Title/Summary/Keyword: 동형성

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Differentiation of Korean isolates of Entamoeba histolytica from Entamoeba dispar (우리 나라에서 분리한 이질아메바(Entamoeba histoItica)와 동형아메바(Entamoebn dispar)의 감별)

  • 최성준;이미정
    • Parasites, Hosts and Diseases
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    • v.34 no.1
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    • pp.15-20
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    • 1996
  • Cysts of Entamoebn histoIMtica are still found from humans in Korea, but notall of the cysts are known as pathogenic. The non-pathogenic strain is regarded as a differenL species, E. nispnr. In this study, Korean isolates of conventional E. histolvticn were subjected for the differentiation by polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) analysis. Human stools were screened by routine microscopic examination, and cyst or trophozoite positive stools were inoculated into Robinson media. The cultivated trophozoites were prepared for DNA extraction, and the DNAs were used for PCR with common primers of Pl gene. The PCR products were divested with 3 restriction enzymes and RFLP was observed. Also anti-sense primers containing the cleavage site of each restriction eWe were designed for differentiation only by PCR. The PCR products of Korean isolates 59,512, YS-6, and YS-27 were spliced by Taq I and Xmnl but not byAccl, and the isolates S1, S3, S11, S15, S16, S17, S20, YS- l7, and YS-44 were spliced by Acc I but not by Taq I and Xmn I. These RFLP pattern correlated well with PCR products by the species specific primers. The findings confirm that the Korean isolates 59,512, YS-6, and YS-27 are E. histolwtico and others are E. dispar. In Korea, most of the asymptomatic cyst carriers are infected by E. dispar, not by E. histolytica. Key words: Entcmoebc histolytica, Entcmoebn dispar Korean isolates, polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP)

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A Study on the Isomorphism and Standardization of School Development Plan and Specialization Plan (「학교발전계획 및 특성화계획」의 동형성 및 표준화 연구)

  • Ha, Ji-hye;Lim, Heon-Wook
    • Journal of Convergence for Information Technology
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    • v.7 no.3
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    • pp.47-53
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    • 2017
  • The university must open the "School Development Plan and Specialization Plan" at the university allimi. The reason for this is the Special Act on the Disclosure of Information by Educational Institutions, enacted on May 25, 2007, and the Plan for Reform of University Reform announced by the Ministry of Education on Mar 28, 2014. Therefore, we examined the similarity and standardized model of the "School Development Plan and Specialization Plan" published by a total of 137 colleges. As a result of the study, only 17(12.4%) of the college produced information in two ways(school development and specialization), and the rest were not. The school development plan presented quantitative indicators such as world number one, The characterization plan presented qualitative indicators such as human. Based on this, standardized research procedures and conception are presented.

Quantum Error Correction Code Scheme used for Homomorphic Encryption like Quantum Computation (동형암호적 양자계산이 가능한 양자오류정정부호 기법)

  • Sohn, Il Kwon;Lee, Jonghyun;Lee, Wonhyuk;Seok, Woojin;Heo, Jun
    • Convergence Security Journal
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    • v.19 no.3
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    • pp.61-70
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    • 2019
  • Recently, developments on quantum computers and cloud computing have been actively conducted. Quantum computers have been known to show tremendous computing power and Cloud computing has high accessibility for information and low cost. For quantum computers, quantum error correcting codes are essential. Similarly, cloud computing requires homomorphic encryption to ensure security. These two techniques, which are used for different purposes, are based on similar assumptions. Then, there have been studies to construct quantum homomorphic encryption based on quantum error correction code. Therefore, in this paper, we propose a scheme which can process the homomorphic encryption like quantum computation by modifying the QECCs. Conventional quantum homomorphic encryption schemes based on quantum error correcting codes does not have error correction capability. However, using the proposed scheme, it is possible to process the homomorphic encryption like quantum computation and correct the errors during computation and storage of quantum information unlike the homogeneous encryption scheme with quantum error correction code.

Word Sense Disambiguation of Polysemy Predicates using UWordMap (어휘지도(UWordMap)를 이용한 용언의 다의어 중의성 해소)

  • Bae, Young-Jun;Ock, Cheol-Young
    • Annual Conference on Human and Language Technology
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    • 2013.10a
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    • pp.167-170
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    • 2013
  • 한국어 어휘의 의미를 파악하기 위하여 어휘의 의미 중의성을 해결하는 것은 중요한 일이다. 본 논문에서는 한국어 다의어 기반의 어휘 의미망과 용언의 논항정보 등의 관계가 포함된 어휘지도(UWordMap)를 사용하여 용언의 의미 중의성 해소에 대한 연구를 진행한다. 기존의 의미 중의성 해소 연구와 같은 동형이의어 단위가 아닌 다의어 단위의 용언 의미 중의성 해소 시스템을 개발하였다. 실험결과 실험말뭉치로 품사 태그 부착 말뭉치를 사용했을 때 동형이의어 단위 정확률은 96.44%였고, 다의어 단위 정확률은 67.65%였다. 실험말뭉치로 동형이의어 태그 부착 말뭉치를 사용했을 때 다의어 단위 정확률은 77.22%로 전자의 실험보다 약 10%의 높은 정확률을 보였다.

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Technical Trend of Fully Homomorphic Encryption (완전동형암호 기술의 연구 동향)

  • Jeong, Myoung In
    • The Journal of the Korea Contents Association
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    • v.13 no.8
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    • pp.36-43
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    • 2013
  • Fully homomorphic encryption is a cryptography system in which coded data can be searched and statistically processed without decryption. Fully homomorphic encryption has accelerated searching speed by minimizing time spent on encryption and decryption. In addition, it is also known to prevent leakage of any data decoded for statistical reasons. Also, it is expected to protect personal information stored in the cloud computing environment which is becoming commercialized. Since the 1970s when fully homomorphic encryption was first introduced, it has been researched to develop the algorithm that satisfy effectiveness and functionality. We will take the reader through a journey of these developments and provide a glimpse of the exciting research directions that lie ahead.

Comparison between Markov Model and Hidden Markov Model for Korean Part-of-Speech and Homograph Tagging (한국어 품사 및 동형이의어 태깅을 위한 마르코프 모델과 은닉 마르코프 모델의 비교)

  • Shin, Joon-Choul;Ock, Cheol-Young
    • Annual Conference on Human and Language Technology
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    • 2013.10a
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    • pp.152-155
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    • 2013
  • 한국어 어절은 많은 동형이의어를 가지고 있기 때문에 주변 어절(또는 문맥)을 보지 않으면 중의성을 해결하기 어렵다. 이런 중의성을 해결하기 위해서 주변 어절 정보를 입력받아 통계적으로 의미를 선택하는 기계학습 알고리즘들이 많이 연구되었으며, 그 중에서 특히 은닉 마르코프 모델을 활용한 연구가 높은 성과를 거두었다. 일반적으로 마르코프 모델만을 기반으로 알고리즘을 구성할 경우 은닉 마르코프 모델 보다는 단순하기 때문에 빠르게 작동하지만 정확률이 낮다. 본 논문은 마르코프 모델을 기반으로 하면서, 부분적으로 은닉 마르코프 모델을 혼합한 알고리즘을 제안한다. 실험 결과 속도는 마르코프 모델과 유사하며, 정확률은 은닉 마르코프 모델에 근접한 것으로 나타났다.

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Verb Sense Disambiguation using Subordinating Case Information (종속격 정보를 적용한 동사 의미 중의성 해소)

  • Park, Yo-Sep;Shin, Joon-Choul;Ock, Cheol-Young;Park, Hyuk-Ro
    • The KIPS Transactions:PartB
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    • v.18B no.4
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    • pp.241-248
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    • 2011
  • Homographs can have multiple senses. In order to understand the meaning of a sentence, it is necessary to identify which sense isused for each word in the sentence. Previous researches on this problem heavily relied on the word co-occurrence information. However, we noticed that in case of verbs, information about subordinating cases of verbs can be utilized to further improve the performance of word sense disambiguation. Different senses require different sets of subordinating cases. In this paper, we propose the verb sense disambiguation using subordinating case information. The case information acquire postposition features in Standard Korean Dictionary. Our experiment on 12 high-frequency verb homographs shows that adding case information can improve the performance of word sense disambiguation by 1.34%, from 97.3% to 98.7%. The amount of improvement may seem marginal, we think it is meaningful because the error ratio reduced to less than a half, from 2.7% to 1.3%.

A Study on the Description of Relationships and Homographs in Terms of Creator and Work in the Korean Thesaurus (한글 시소러스에서 저자와 저작에 대한 관계 설정과 동형 이의어의 기술)

  • Han, Sang-Kil;Choi, Suk-Doo
    • Journal of the Korean Society for Library and Information Science
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    • v.45 no.4
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    • pp.139-155
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    • 2011
  • The failure of distinguishing homographs in describing relations of individual authors and relations of authorship(i.e. distinction of persons with the same name or persons of the same literary author's name) will cause difficulties of retrieving exact information. It is because relations of automorphism cannot be formed between the two sets mentioned above. Therefore, it is ultimately necessary to set up the criteria or tools to distinguish homographs in order to retrieve more exact information. In the past, some efforts were made to develop authority data in order to solve the homograph problems by individual libraries, documents and portal sites in Korea. It is well understood that developing authority data by an individual institution was very difficult with no criteria or no rules to clarify the homograph problems at the national level. This study is to develop ways of recognizing individual names including subject words and proper nouns. The results of the study will present methods of distinguishing and describing homographs between individual author sets, and authorship sets particularly focused on the areas of arts and popular culture.

Hangul-Hanja Translator Based on Semantic Analysis (의미 분석에 기반을 둔 한글-한자 변환 시스템)

  • Jung, Il-Hyung;Lee, Jong-Hyeok
    • Annual Conference on Human and Language Technology
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    • 1992.10a
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    • pp.85-93
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    • 1992
  • 본 논문은 한글-한자 변환에 있어서 여러 대응 한자를 갖는 동형이의어의 모호성 해소 방법을 제안한다. 기존의 변환 방법은 사용자의 개입으로 이루어지므로, 사용자에게 많은 부담을 주고 변환 효율을 떨어뜨린다. 한자선택에 있어서 동형이의어 문제의 근본적 해결을 위해, 본 시스템에서는 의미 분석을 이용한 한글-한자 변환기를 제안한다. 이를 위해 격문법과 관련어 지식 베이스(thesaurus)를 사용한다. 격문법을 사용하여 서술어를 중심으로 관련된 격틀의 의미를 분석한다. 그리고 합성어의 경우에 합성어의 구성 형태에 따라 격문법을 사용하거나 관련어 지식 베이스에서의 의미 근접성을 사용한다. 본 논문은 이와 같이 의미 분석 및 개념 정보를 기반으로 하는 동형이의어의 모호성 해결 방안을 제시하고 이를 반영한 한글-한자 변환 시스템의 설계 및 구현에 관하여 기술한다.

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Homonym Identification Using Korean Pre-trained Model KE-T5 (한국어 사전학습 모델 KE-T5 기반 동형이의어 구별)

  • Moon, Seona;Seo, Hyeon-Tae;Shin, Saim;Kim, San
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.507-508
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    • 2021
  • 최근 한국어 자연어처리 과제에서 대형 언어 모델을 통해 다양한 언어처리 작업에 대한 연구가 활발히 이루어지고 있다. 특히 동형이의어를 구분하는 작업은 문장의 문법성을 정확히 판단하고 비교해야 되기 때문에 어려운 작업이다. KE-T5는 큰 규모의 한국어를 통해 학습된 한국어 대형 언어 모델로 대부분의 자연어처리 과제에서 활용할 수 있으며 복잡한 언어처리 작업에서 높은 성능을 기대할 수 있다. 본 논문에서는 큰 규모의 한국어를 통해 학습된 KE-T5를 활용하여 동형이의어 구별 문제를 수행하고 평가한다.

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