• Title/Summary/Keyword: multi-language

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A Methodological Study on Ecological Economic Evaluation of a Multipurpose Dam Construction Using Emergy Concept (에머지(Emergy) 개념을 이용한 다목적댐 건설의 생태경제학적인 평가방법에 관한 연구)

  • Kang, Dee Seok;Park, Seok Soon
    • Journal of Environmental Impact Assessment
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    • v.8 no.2
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    • pp.45-51
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    • 1999
  • Emergy concept was used to evaluate the contributions of a dam construction to the real wealth of our economy. A dam that is proposed as a multi-purpose dam was used to illustrate emergy evaluation methodology. Models for emergy evaluation were constructed with energy systems language, a symbolic modeling language which presents network properties of systems holistically. Water supply was the most important contribution in terms of emergy, which reflects that the dam is proposed for stable water supply to a local region. Generation of electricity was the second in emergy benefits of the dam. Emergy costs were more evenly distributed among the costs which would occur as a result of the dam construction. Emergy yield ratio was 1.30 if sediments are not included, and 1.15 if sediments are included, which results in net yield in both cases. The ratio would, however, fall below 1.0 if rare species within the system boundary are lost as a result of the dam construction because of the high emergy value included in biotic species, which means that emergy costs will be greater than emergy benefits. This study illustrated a new methodology in environmental impact assessment to better manage our environments in an age of diminishing resources.

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The Effects of Psychological Well-Being of Married Immigrant Women on Parenting Efficacy (여성 결혼이민자의 심리적 안녕감이 양육효능감에 미치는 영향)

  • Lee, Sung Hee;Park, Ung Im
    • Korean Journal of Child Studies
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    • v.37 no.2
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    • pp.143-155
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    • 2016
  • Objective: The purpose of the study was to investigate the effects of psychological well-being on married immigrant women's parenting efficacy. Methods: The participants consisted of 145 married immigrant mothers who were members of multi-cultural family support centers in Andong, Young-ju, Uiseung, and Munkyung cities in Gyeongsangbuk-do province. Results: The main results are as follows. First, the levels of language competence and education were significantly related to psychological well-being, suggesting that the level of language competence as well as the level of education could be main factors for psychological well-being. Further, numbers of children and monthly household income were significantly related to parenting efficacy. Second, psychological well-being was correlated with parenting efficacy of married immigrant women, demonstrating that psychological well-being was the most effective variable for parenting efficacy. Third, self-acceptance, environmental mastery, and personal growth in the psychological well-being significantly predicted parenting efficacy. Conclusion: These findings suggested that we should reconsider the importance of psychological well-being in supporting programs for parenting.

CNN-based Distant Supervision Relation Extraction Model with Multi-sense Word Embedding (다중-어의 단어 임베딩을 적용한 CNN 기반 원격 지도 학습 관계 추출 모델)

  • Nam, Sangha;Han, Kijong;Kim, Eun-Kyung;Gwon, Seong-Gu;Jeong, Yu-Seong;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 2017.10a
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    • pp.137-142
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    • 2017
  • 원격 지도 학습은 자동으로 매우 큰 코퍼스와 지식베이스 간의 주석 데이터를 생성하여 기계 학습에 필요한 학습 데이터를 사람의 손을 빌리지 않고 저렴한 비용으로 만들 수 있어, 많은 연구들이 관계 추출 문제를 해결하기 위해 원격 지도 학습 방법을 적용하고 있다. 그러나 기존 연구들에서는 모델 학습의 입력으로 사용되는 단어 임베딩에서 단어의 동형이의어 성질을 반영하지 못한다는 단점이 있다. 때문에 서로 다른 의미를 가진 동형이의어가 하나의 임베딩 값을 가지다 보니, 단어의 의미를 정확히 파악하지 못한채 관계 추출 모델을 학습한다고 볼 수 있다. 본 논문에서는 원격 지도 학습 기반 관계 추출 모델에 다중-어의 단어 임베딩을 적용한 모델을 제안한다. 다중-어의 단어 임베딩 학습을 위해 어의 중의성 해소 모듈을 활용하였으며, 관계 추출 모델은 문장 내 주요 특징을 효율적으로 파악하는 모델인 CNN과 PCNN을 활용하였다. 본 논문에서 제안하는 다중-어의 단어 임베딩 적용 관계추출 모델의 성능을 평가하기 위해 추가적으로 2가지 방식의 단어 임베딩을 학습하여 비교 평가를 수행하였고, 그 결과 어의 중의성 해소 모듈을 활용한 단어 임베딩을 활용하였을 때 관계추출 모델의 성능이 향상된 결과를 보였다.

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A Study on the Handwritten Korean Numeric Recognition using a Backpropagation Learning Neural Network (역전파 학습 신경망을 이용한 한글 숫자 인식에 관한 연구)

  • Park, Chang-Min;Park, Kwi-Soon;Kim, Dae-Won;Lee, Dong-Choon;Kim, Myeng-Won;Bae, Hyun-Joo;Cha, Eui-Young
    • Annual Conference on Human and Language Technology
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    • 1989.10a
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    • pp.137-141
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    • 1989
  • 본 논문에서는 신경망 구조의 한 모델인 feed-forward multi-layered network에 역전파 학습(back-propagation learning) 기법을 이용하여 필기체 한글 숫자를 인식하고 그 가능성을 보였다. 문자 인식에 있어 입력 대상의 모양이 왜곡되거나, 대상의 크기 혹은 위치의 변화 등과 같은 잡음 (noise)에 대해서 정확히 대상을 인식하는 데는 대상의 구조 추출에 크게 관여되므로 한글의 구조 추출에 적합하다고 생각되는 bar mask 투사법을 제안하였다. 모델의 학습을 필기체 한글 숫자 16자의 입력 패턴과 타겟 ( target) 입력의 쌍을 이용해 학습시켰다. 또한, 모델의 인식 정도를 측정해 보기 위해 시험패턴을 적용하여 훈련된 패턴과 훈련되지 않은 패턴간의 인식률을 비교하여 보았다.

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The Structure of Polysemy: A study of multi-sense words based on WordNet

  • Lin, Jen-Yi;Yang, Chang-Hua;Tseng, Shu-Chuan;Huang, Chu-Ren
    • Proceedings of the Korean Society for Language and Information Conference
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    • 2002.02a
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    • pp.320-329
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    • 2002
  • The issues in polysemy with respect to the verbs in WordNet will be discussed in this paper. The hypernymy/hyponymy structure of the multiple senses is observed when we try to build a bilingual network for Chinese and English. There are several types of polysemic patterns and a co-hypernym may have the same word form as its subordinates. Fellbaum (2000) dubbed autotroponymy that the verbs linked by mailer relation share the same verb form. However, her syntactic criteria seem not compatible to the hierarchies in WN. Either the criteria or the network should be reconducted. For most verbs in WN 1.7, polysemous relations are unlikely to extend over 3 levels of IS-A relation. Highly polysemous verbs are more complicated and may be involved in certain semantic structures. Semi-automatic sense grouping may be helpful for multimlinguital information retrieveal.

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A Study on The Color Examination and Color Planning in the Different Type of Classroom (학교 교실의 용도별 색채분포 및 색채계획에 관한 연구)

  • 김은정;김기환
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2003.05a
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    • pp.65-68
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    • 2003
  • The purpose of this study is examine the color planning in the different type of classroom to establish interior color planning. This study also uses environmental planning and practical use of basic data for color planning to future school facilities. The summary of this study is as followed. The primary school and middle school classrooms as well as the open space classrooms floor color recommended of brown and the primary school wall color is light yellow, middle school wall color is light yellow and brown. The high school classroom color is recommended brown and wall color to light yellow and green system. The recommended floor color of primary school which includes in computer room and language study room, library of the multi-purpose of media room recommended are gray, brown and pink. The recommended wall color in primary school is light gray. The middle school floor color propose gray and light brown and wall recommended color is light brown, gray, ivory with the high school the computer room, language study room and library. The floor color is recommended gray, green and the wall propose blue. Moreover, recognize that importance of color effectiveness in school interior facilities considering with Interior covering material in class room.

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Quantifying L2ers' phraseological competence and text quality in L2 English writing (L2 영어 학습자들의 연어 사용 능숙도와 텍스트 질 사이의 수치화)

  • Kwon, Junhyeok;Kim, Jaejun;Kim, Yoolae;Park, Myung-Kwan;Song, Sanghoun
    • 한국어정보학회:학술대회논문집
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    • 2017.10a
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    • pp.281-284
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    • 2017
  • On the basis of studies that show multi-word combinations, that is the field of phraseology, this study aims to examine relationship between the quality of text and phraseological competence in L2 English writing, following Yves Bestegen et al. (2014). Using two different association scores, t-score and Mutual Information(MI), which are opposite ways of measuring phraseological competence, in terms of scoring frequency and infrequency, bigrams from L2 writers' text scored based on a reference corpus, GloWbE (Corpus of Global Web based English). On a cross-sectional approach, we propose that the quality of the essays and the mean MI score of the bigram extracted from YELC, Yonsei English Learner Corpus, correlated to each other. The negative scores of bigrams are also correlated with the quality of the essays in the way that these bigrams are absent from the reference corpus, that is mostly ungrammatical. It indicates that increase in the proportion of the negative scored bigrams debases the quality of essays. The conclusion shows the quality of the essays scored by MI and t-score on cross-sectional approach, and application to teaching method and assessment for second language writing proficiency.

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A Parallel Speech Recognition Model on Distributed Memory Multiprocessors (분산 메모리 다중프로세서 환경에서의 병렬 음성인식 모델)

  • 정상화;김형순;박민욱;황병한
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.5
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    • pp.44-51
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    • 1999
  • This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

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Resolving Multi-Translatable Verbs Japanese-TO-Korean Machine Translation

  • Kim Jung-In;Lee Kang-Hyuk
    • Journal of Korea Multimedia Society
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    • v.8 no.6
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    • pp.790-797
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    • 2005
  • It is well-known that there are many similarities between Japanese and Korean language. For example, the order of words and the nature of the grammatical conjugation of both languages are almost the same. Another similarity is the frequent omission of the subject from a sentence. Moreover, both languages have honorific expressions and the identical concept for expressing nouns in terms of Chinese characters. Using these similarities, we have developed a word-to-word translation system which does away with any deep level analysis of syntactic and semantic structures of the two languages. If we use these similarities, the direct translation method is superior to the internal language translation method or transfer-based translation method. Although the MT system based on the direct translation method is more easily developed than the ones based on other methods, it may have a lot of difficulties when it tries to select the appropriate target word from ambiguous source verbs. In this paper, we propose a new algorithm to extract the meaning of substantives and to make use of the order of the extracted meaning. We could select $86.5\%$ appropriate verbs in the sample sentences from IPAL-verb-dictionary. $13.5\%$ indicates the cases in which we could not distinguish the meaning of substantives. We are convinced, however, that the succeeding rate can be increased by getting rid of the meaning of verbs thatare not used so often.

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News Clustering and Multi-Document Summarization for Real-time Issue Analysis (실시간 이슈 분석을 위한 뉴스 군집화 및 다중 문서 요약)

  • Yu, Hongyeon;Lee, Seungwoo;Ko, Youngjoong
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.132-137
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    • 2018
  • 뉴스 기반의 실시간 이슈 분석을 위해서는 실시간으로 생성되는 다중 뉴스 기사 집합을 입력으로 받아 점증적으로 군집화 하고, 각 군집별 정보를 자동으로 요약하는 기술이 필요하다. 기존에는 정적인 데이터 기반의 군집화와 요약 각각에 대한 연구는 활발히 진행되고 있지만, 실시간으로 입력되는 대량의 데이터를 위한 점증적인 군집화와 요약에 대한 연구는 매우 부족하다. 따라서 본 논문에서는 실시간으로 입력되는 대량의 뉴스 기사 집합을 분석하기 위한 점증적이고 계층적인 뉴스 군집화 및 다중 문서 요약 방법을 제안한다. 평가를 위해서 2016년 10월, 11월 두 달간의 실제 데이터를 사용 하였으며, 전문 교육을 받은 연구원들이 Precision at k 기반의 정성평가를 진행하였다. 그 결과, 자동으로 생성된 12개의 군집에서 군집 성능은 평균 66% (상위계층 $l_1$: 82%, 하위계층 $l_2$: 43%), 요약 성능은 평균 92%를 얻었다.

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