• 말소리와 음성과학
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• 제7권4호
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• pp.49-55
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• 2015

It is argued in this paper that, in determining semantic similarity, Korean words should be recategorized with a focus on the semantic relation to ontology in light of cross-linguistic morphological variations. It is proposed, in particular, that Korean semantic similarity should be measured on three tracks, human judgements track, relatedness track, and cross-part-of-speech relations track. As demonstrated in Yang et al. (2015), GloVe, the unsupervised learning machine on semantic similarity, is applicable to Korean with its performance being compared with human judgement results. Based on this compatability, it was further thought that the model's performance might most likely vary with different kinds of specific relations in different languages. An attempt was made to analyze them in terms of two major Korean-specific categories involved in their lexical and cross-POS-relations. It is concluded that languages must be analyzed by varying methods so that semantic components across languages may allow varying semantic distance in the vector space models.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.579-583
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• 2001

In the area of data clustering in high dimensional space, one of the difficulties is the time-consuming process for computing vector similarities. It becomes worse in the case of the agglomerative algorithm with the group-average link and mean centroid method, because the cluster similarity must be recomputed whenever the cluster center moves after the merging step. As a solution of this problem, we present an incremental method of similarity computation, which substitutes the scalar calculation for the time-consuming calculation of vector similarity with several measures such as the squared distance, inner product, cosine, and minimum variance. Experimental results show that it makes clustering speed significantly fast for very high dimensional data.

• 대한전기학회논문지:전력기술부문A
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• 제53권4호
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• pp.227-233
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• 2004

In stressed power system due to the presence of increased nonlinearity and the existence of nonlinear modal interactions. there exist some limitations to the use of conventional linear system theory to identify the optimum sites for a controller. This paper suggests an approach based on the method of normal forms to identify the optimum sites for controllers with incorporating the nonlinear interaction . In this paper, nonlinear participation factors and coupling factors are proposed as measures of the nonlinear interactions, and identification procedure of optimum sites for a controller is also proposed. The proposed procedure is applied to the 10-generator New England System and the KEPCO System in the year of 2010, and the results illustrate its capabilities.

• 재활복지공학회논문지
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• 제9권3호
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• pp.245-250
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• 2015

스마트 폰과 개인 휴대정보 단말기와 같은 장치는 일상생활에서 중요한 역할을 담당한다. 본 논문에서는 물리적 활동의 모니터링을 위해 신호벡터크기(signal vector magnitude)와 적응적인 임계값 처리에 기반한 걸음수 검출 알고리즘을 제안한다. 알고리즘은 스마트 폰에 내장된 가속도 센서와 중력 센서를 사용하여 걸음수를 측정한다. 실험결과 제안한 알고리즘이 스마트 폰의 어플에 비해 정확도와 적응성에서 좋은 성능을 나타내었다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제53권4호
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• pp.227-227
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• 2004

In stressed power system due to the presence of increased nonlinearity and the existence of nonlinear modal interactions. there exist some limitations to the use of conventional linear system theory to identify the optimum sites for a controller. This paper suggests an approach based on the method of normal forms to identify the optimum sites for controllers with incorporating the nonlinear interaction . In this paper, nonlinear participation factors and coupling factors are proposed as measures of the nonlinear interactions, and identification procedure of optimum sites for a controller is also proposed. The proposed procedure is applied to the 10-generator New England System and the KEPCO System in the year of 2010, and the results illustrate its capabilities.

• 응용통계연구
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• 제23권1호
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• pp.151-165
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• 2010

영상은 잡음센서이나 채널 전송에러에 의해 생기는 임펄스 잡음에 의해 자주 오염된다. 본 논문은 영상에서 이런 임펄스 잡음을 제거하는 방법에 대해 논의하고자 한다. 제안된 잡음제거는 SVM(Support Vector Machine)과 개선된 Adaptive Median 필터에 의해 이루어진다. SVM에 의해 영상에서 잡음픽셀여부를 검출하고 검출된 잡음픽셀은 개선된 Adaptive Median 필터에 의해 새로운 픽셀값으로 대체한다. 제안된 방법의 성능을 평가하기 위해 영상 실험을 통하여 salt-and-pepper 임펄스 잡음과 random-valued 임펄스 잡음을 고려하여 기존의 잡음제거 방법들과 정성적이고 MAE, PSNR를 통한 정량적인 비교를 하였다. 실험결과 제안된 방법은 잡음 제거와 미세한 부분에 대한 보존력이 뛰어나고 특히, 많이 오염된 영상에 대해서도 상당한 잡음제거 성능을 보였다.

• Journal of Plant Biotechnology
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• 제6권4호
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• pp.221-227
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• 2004

Protocol was established for production of virus free healthy seeds using meristem ($0.3-0.5\;\cal{mm}$ in size) culture and field management under net house condition in tomato. The isolated meristem was found well established in MS liquid medium containing $0.1\;\cal{mg}\;1^{-1}\;of\;GA_3$. For shoot and root development either from primary meristem or from nodal segment of meristem derived plants, semisolid MS medium having $0.5\;\cal{mg}\;1^{-1}$ of IBA was found most effective. The elimination of the studied viruses (ToMV, CMV, ToLCV) in meristem-derived plants was confirmed by DAS-ELISA test. For field management of the virus eradicated meristem-derived plants, use of net house was found very effective measures to check viral vector visit and eventually infection. The meristem-derived plants were vigor and high yielder than the native seed derived plants and produced healthy seeds. Due to stop vector visit, no viral symptoms were observed in both $R_1\;and\;R_2$ plants cultivated in net house condition. Starting of viral infestation was observed in $R_2$ generation when they were planted in open house condition without control of vector visit. Therefore, for management of viral diseases, use of virus free meristem derived plantlets and their subsequent cultivation in soil under net house condition without using any vector killing insecticide can be recommended for producing healthy seeds in tomato. The developed protocol for environmentally healthy tomato seed production in Bangladesh may be used in the countries having similar tropical like environment conducive for viral vector visit.

• Journal of applied mathematics & informatics
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• 제39권5_6호
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• pp.895-918
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• 2021

Human African Trypanosomiasis (HAT) also known as sleeping sickness, is a neglected tropical vector borne disease caused by trypanosome protozoa transmitted by bites of infected tsetse fly. The basic reproduction number, R₀ derived using the next generation matrix method which shows that the disease persists in the population if the value of R₀ > 1. The numerical simulations of optimal control model carried out to determine the control strategy that can combat HAT under the minimum cost. The results indicate that, the use of both education campaign, treatment and insecticides are more efficient and effective to eliminate HAT in African community but too costly. Furthermore, the cost-effectiveness of the control measures (education campaign, treatment and insecticides) were determined using incremental cost-effectiveness ratio (ICER) approach and the results show that, the use of education and treatment of infected people as the best cost effective strategy compared to other strategies.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1438-1444
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• 2018

Recently, with the development of Internet technologies and propagation of smart devices, use of microblogs such as Facebook, Twitter, and Instagram has been rapidly increasing. Many users check for new information on microblogs because the content on their timelines is continually updating. Therefore, clustering algorithms are necessary to arrange the content of microblogs by grouping them for a user who wants to get the newest information. However, microblogs have word limits, and it has there is not enough information to analyze for content clustering. In this paper, we propose a semantic-based K-means clustering algorithm that not only measures the similarity between the data represented as a vector space model, but also measures the semantic similarity between the data by exploiting the TagCluster for clustering. Through the experimental results on the RepLab2013 Twitter dataset, we show the effectiveness of the semantic-based K-means clustering algorithm.

• 한국정보통신학회논문지
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• 제20권3호
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• pp.471-476
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• 2016

본 논문에서는 음성 특성 지표를 이용한 음성 인식 성능 예측 실험의 내용을 소개한다. 선행 실험에서 효과적인 음성 인식 성능 예측을 위해 대표적인 음성 인식 성능 지표인 단어 오인식률과 상관도가 높은 여러 가지 특성 지표들을 조합하여 새로운 성능 지표를 제안하였다. 제안한 지표는 각 음성 특성 지표를 단독으로 사용할 때 보다 단어 오인식률과 높은 상관도를 나타내 음성 인식 성능을 예측하는데 효과적임을 보였다. 본 실험에서는 이 결과를 근거하여 조합에 사용된 음성 특성 지표를 채택하여 4차원 특징 벡터를 생성하고 GMM 기반의 음성 인식 성능 예측기를 구축한다. 가우시안 요소를 증가시키며 실험한 결과 제안된 시스템은 babble 잡음, 자동차 잡음에서 모두 SNR이 낮을수록 단어 오인식률을 높은 확률로 예측함을 확인하였다.