• 한국음향학회지
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• 제9권6호
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• pp.22-28
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• 1990

최근에 음성합성 기술이 발전됨에 따라 이러한 기술을 이용한 새로운 통신 서비스가 등장하고 있으며 그 표준 설정에 있어서 음성 품질은 아주 중요한 요인이 된다. 따라서, 시스템 알고리즘의 진단 적 평가 및 평가치의 상호 비교를 위해 품질 평가방법을 개발하는 것은 매우 중요하다. 본 논문에서는 규칙 합성음성의 이해성 평가를 위한 기본적 사항들과 개념을 기술하고 ,이해성 평가에 사용되는 단어 표를 구성하는 방법과 단어표를 제안하였다.

• 한국조리학회지
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• 제17권3호
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• pp.20-32
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• 2011

본 연구는 향토음식점에 대한 구전정보에 대한 고객행동을 규명하기 위하여 수행하였다. 설문조사는 전북지역 거주자 500명을 대상으로 총 455부(회수율 91.0%)를 분석에 이용하였다. 자료는 SPSS 12.0 프로그램을 이용하여 분석하였다. 연구결과 향토음식점에 대한 구전정보 중 가장 많이 활용하고 있는 정보원에 있어서는 '직접 경험해 본 주위사람들의 추천'$(M=3.57{\pm}1.24$)과 '주변사람들을 통한 구전'($M=3.52{\pm}1.20$)이 높게 나타났고, 향토음식점에 대한 구전정보를 구할 때 소비자들이 중요시하는 속성에 대해 분석한 결과에서는 '음식의 맛'($M=4.16{\pm}1.15$), '음식점의 종사원 서비스'($M=3.79{\pm}1.11$)를 가장 중요시하는 것으로 나타났다. 향토음식점을 주위사람들에게 추천을 하는 동기에 대해 분석한 결과 '맛, 영양, 품질 모두 현지에서만이 유지할 수 있으므로'($M=3.53{\pm}1.10$)가 가장 높게 나타났고, '향토음식을 통해 지역 방문 기약을 오래도록 남기기 위하여'($M=3.52{\pm}1.03$), '향토음식을 구전을 통해 적극적으로 알릴 필요가 있으므로'($M=3.51{\pm}1.06$)순으로 나타났다. 이는 소비자의 향토음식점에 대한 추천이 음식 자체의 품질과 방문지역의 특성에 있음 보여준다. 연구결과 향토음식점에 대한 고객행동에 있어 구전정보의 중요성을 시사해 주고 있다.

• 한국항해항만학회지
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• 제41권3호
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• pp.109-118
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• 2017

주제어(key word, KW)는 해양사고의 주요한 원인을 간단하게 표현하기 위한 단어들의 집합으로 해양안전심판원의 심판관들이 작성한다. KW는 심판관들의 서로 다른 주관적인 견해 때문에 일관성 유지가 어렵고, KW의 수가 너무 많은 문제점이 있다. 이러한 문제를 해결하기 위해서는 최적화된 최소의 공통단어(common word, CW)를 이용한 체계적인 KW 구축 프레임이 필요하다. 본 연구의 목적은 체계적인 KW 구축 프레임 개발에 필요한 CW을 도출하는데 있다. 이러한 목적을 달성하기 위하여 본 연구에서는 파레토(Pareto) 분포함수와 파레토 지수를 이용한 최적의 최소 CW 도출방법을 제안하였다. 총 2,642개의 KW을 수집한 후, 수집한 KW의 세부 단어와 이들의 빈도를 갖는 데이터 세트에서 총 56개의 특징적인 CW를 식별하였다. 56개의 특징적인 CW를 이용한 단어 축소실험을 통해서 평균 58.5%의 축소율을 획득하였고, 축소율에 따라서 추정한 CW는 파레토 차트로 검증하였다. 이를 통해서 체계적인 KW 구축 프레임 개발이 가능할 것으로 기대된다.

• 한국중재학회지:중재연구
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• 제23권3호
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• pp.1-23
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• 2013

Form requirements particularly for arbitration clauses are widely perceived as an obstacle for efficiently resolving disputes on an international level. The paper discusses the recent suggestion that the freedom of form principle under Art. 11 CISG extended to arbitration, forum selection, or choice of law clauses in international sales contracts and thus superseded any and all formal requirements in this regard. After analysing national and international form requirements with regard to said clauses, the authors elaborate that while dispute clauses are indeed encompassed by the CISG's scope of application, freedom of form under the CISG was neither intended to nor should it apply to dispute clauses. This result is further confirmed by the interplay of the CISG with other international conventions, first and foremost the 1958 New York Convention, as well as a careful analysis of the so called most-favourable-law-approach.

• 한국수정란이식학회지
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• 제11권1호
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• pp.1-6
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• 1996

다배란 수정란이식(MOET)과 체외수정(IVF)기술을 이용한 육종체계에서 예상되는 유전적 개량량을 여러 집단의 크기에서 비교한 결과 체외수정기술이 MOET육종기술보다 특히 개량대상 유전력이 낮을때 훨씬 효율적으로 나타났다. 그러나 유전력이 높아지면 (h$^2$=0.3, 0.5), MOET와 IVF간의 상대적 차이는 미진하게 나타났다. 체외수정을 이용한 육종기술에서 암컷의 선발 강도는 대단히 높일 수 있는 반면 난자의 회수율이 많을수록 상대적으로 수컷에 대한 선발 강도는 낮아진다. 그 이유는 한 가계에서 근친을 피하기 위해 한 마리의 수컷만 선발해야 하므로 수소의 선발강도는 난자의 회수율이 높을수록 상대적으로 낮아진다. 여러 수준의 난자회수율(10, 20, 30, 50, 100)중에서 30일 때 가장 높은 유전적 개량을 나타내었다. (Key word: MOET, IVF,selection responses)

• 대한음성학회:학술대회논문집
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• 대한음성학회 2005년도 추계 학술대회 발표논문집
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• pp.103-106
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• 2005

In this paper, we propose a language modeling approach to improve the performance of a large vocabulary continuous speech recognition system. The proposed approach is based on the active learning framework that helps to select a text corpus from a plenty amount of text data required for language modeling. The perplexity is used as a measure for the corpus selection in the active learning. From the recognition experiments on the task of continuous Korean speech, the speech recognition system employing the language model by the proposed language modeling approach reduces the word error rate by about 6.6 % with less computational complexity than that using a language model constructed with randomly selected texts.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1029-1035
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• 2019

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

• Human Ecology Research
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• 제60권4호
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• pp.625-643
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• 2022

The purpose of this study was to explore the trends and core keywords of the secondary school home economics teacher selection test using content analysis and text network analysis. The sample comprised texts of the secondary school home economics teacher 1st selection test for the 2017-2022 school years. Determination of frequency of occurrence, generation of word clouds, centrality analysis, and topic modeling were performed using NetMiner 4.4. The key results were as follows. First, content analysis revealed that the number of questions and scores for each subject (field) has remained constant since 2020, unlike before 2020. In terms of subjects, most questions focused on 'theory of home economics education', and among the evaluation content elements, the highest percentage of questions asked was for 'home economics teaching·learning methods and practice'. Second, the network of the secondary school home economics teacher selection test covering the 2017-2022 school years has an extremely weak density. For the 2017-2019 school years, 'learning', 'evaluation', 'instruction', and 'method' appeared as important keywords, and 7 topics were extracted. For the 2020-2022 school years, 'evaluation', 'class', 'learning', 'cycle', and 'model' were influential keywords, and five topics were extracted. This study is meaningful in that it attempted a new research method combining content analysis and text network analysis and prepared basic data for the revision of the evaluation area and evaluation content elements of the secondary school home economics teacher selection test.

• 산업공학
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• 제13권3호
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• pp.296-305
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• 2000

In supply chains, coordination between a manufacturer and suppliers is regarded as the most important issue when partnership of organizations is considered. Since the suppliers are external to the manufacturer and poor coordination between them results in excessive delays and ultimately leads to poor customer service, manufacturers need a new methodology to select suppliers and to manage and enhance the partnership between manufacturer and suppliers. We suggest a methodology that extends knowledge obtained from the supplier selection process to the supplier management process. We reserved a word, the supplier selection and management system (SSMS) for this methodology. In this paper, we explain how the SSMS is applied to a real supply chain. The methodology identifies the managerial criteria using information derived from supplier selection process and makes use of them in the supplier management process. These managerial criteria include key criteria that are major criteria required by the manufacturer for the best quality of parts from suppliers according to the character of each part, and weak criteria that show the shortcomings of selected suppliers as compared with alternative suppliers with regard to each criterion. The effectiveness of supplier management with managerial criteria was verified by a t-test and a correlation analysis with data collected and hypothesized from a Korean air-conditioner manufacturer.

• 음성과학
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• 제8권4호
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• pp.17-33
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• 2001

In this paper, we implement the large variable vocabulary speech recognition system, which is characterized by no additional pre-training process and no limitation of recognized word list. We have designed the system in order to achieve the high recognition rate using the decision tree based state tying algorithm and in order to reduce the processing time using the gaussian selection based variable flooring algorithm, the limitation algorithm of the number of nodes and ENNS algorithm. The gaussian selection based variable flooring algorithm shows that it can reduce the total processing time by more than half of the recognition time, but it brings about the reduction of recognition rate. In other words, there is a trade off between the recognition rate and the processing time. The limitation algorithm of the number of nodes shows the best performance when the number of gaussian mixtures is a three. Both of the off-line and on-line experiments show the same performance. In our experiments, there are some differences of the recognition rate and the average recognition time according to the distinction of genders, speakers, and the number of vocabulary.