• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.331-348
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• 2019

Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.519-524
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• 2010

In this paper, we will introduce our approach for composing operation based on user tasks. It is based on Service Component Architecture (SCA). In addition, we developed ontology based on OWL and the MIT process handbook, called u-TO(universal task ontology), which can be used for users describing and specifying semantically their needs. We represent the hierarchy of tasks, and classify tasks according to views in u-TO. It aims at facilitating the modeling of complex demands or systems without regarding details of technical aspects of underlying infrastructure.

• Corrugated packaging logistics
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• s.87
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• pp.66-85
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• 2009

기존 골판지는 제품보호나 수송을 목적으로 사용하나, 소비자의 소비 패턴의 변화 등 시장동향에 따라 포장재의 고급화, 그래픽과 인쇄성의 강조 및 제품수송비용을 절감시킬 수 있는 포장재로서 마이크로플루트 골판지 포장재가 대두되고 있다. 이에 한국골판지포장공업협동조합은 3년여에 걸쳐 조합원사 및 서울대학교와 연계하여 연구과제를 수행하였으며, 그 연구 결과물을 알아보고자 한다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.546-550
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• 2010

In this paper, we propose a method for the postprocessing of cursive script recognition in Wine Label Images. The proposed method mainly consists of three steps: combination matrix generation, character combination filtering, string matching. Firstly, the combination matrix generation step detects all possible combinations from a recognition result for each of the pieces. Secondly, the unnecessary information in the combination matrix is removed by comparing with bigram of word in the lexicon. Finally, string matching step decides the identity of result as a best matched word in the lexicon based on the levenshtein distance. An experimental result shows that the recognition accuracy is 85.8%.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.127-129
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• 2010

본 논문에서는 다양한 코퍼스를 통해 언어를 학습하는 과정을 모델링하여 무감독학습(Unsupervised learning)으로 문법적 패턴을 습득하는 방법론을 소개한다. 제안 방법에서는 적은 수의 특성 조합으로 잠재적 패턴의 부분만을 표현한 후 표현된 규칙을 조합하여 유의미한 문법적 패턴을 탐색한다. 본 논문에서 제안한 방법은 베이지만 추론(Bayesian Inference)과 MCMC (Markov Chain Mote Carlo) 샘플링에 기반하여 특성 조합을 유의미한 문법적 패턴으로 정제하는 방법으로, 랜덤하이퍼그래프(Random Hypergraph) 모델을 이용하여 많은 수의 하이퍼에지를 생성한 후 생성된 하이퍼에지의 가중치를 조정하여 유의미한 문법적 패턴을 탈색하는 방법론이다. 우리는 본 논문에서 유아용 비디오의 스크립트를 이용하여 다양한 유아용 비디오 스크립트에서 문법적 패턴을 습득하는 방법론을 소개한다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.867-876
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• 2013

Metabolic syndrome has been known as a major factor of cardiovascular disease. Several metabolic disorders, particularly chronic disease is complex, and from individuals that appear in our country, the prevalence of the metabolic syndrome is increasing gradually. Therefore, this study, using a multi-factor dimensionality reduction method, checks the major single risk factor of metabolic syndrome and suggests a new diagnosis results of metabolic syndrome. Data of 3990 adults who responded to all the questionnaires of health interview are used from the database of the 5th Korea national health and nutrition examination survey conducted in 2010. As the result, the most dangerous single risk factor for metabolic syndrome was waist circumference and the most dangerous combination factors were waist circumference, triglyceride, and hypertension. This is the result of a new diagnosis of the metabolic syndrome. Especially, waist circumference, low HDL-cholesterol and hypertension were the most dangerous combination for male. In particular, the combination of waist circumference, triglyceride and diabetes was dangerous for obese people.

• Journal of KIISE:Software and Applications
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• v.36 no.10
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• pp.800-815
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• 2009

Recently, Web services based service-oriented architecture is widely used to integrate effectively various applications distributed on the networks. In the service-oriented architecture BPEL as a standard modeling language for the business processes provides the way to integrate various services provided by applications. Over the past few years, some types of studies have been made on testing compatibility of services and on discriminating and tracing of the business processes in the services composition. Now a lot of studies about the services composition with BPEL are going on. However there were few efforts to solve the problems caused by the services composition. Especially, there is no effort to evaluate whether a composite service is reliable and whether it is robust against to exceptional situations. In this paper, we suggest a test framework and a testing method for robustness of the composite service written in WS-BPEL. For this, firstly we extract some information from the BPEL process and the participant services. Next, with the extracted information we construct the virtual testing environment that generates various faults and exceptional cases which may be raised within the real services. Finally the testing work for robustness of a composite service is performed on the test framework.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.3
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• pp.25-34
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• 1993

The long-term behavior, such as in excavation problems of weak medium, can be dealt with by the elasto-viscoplasticity models. In this paper, a combined formulation of elasto-viscoplasticity using boundary elements and finite elements without using internal cells is presented. The domain integral introduced due to the viscoplastic stresses is transformed into a boundary integral applying direct integration in cylindrical coordinates. The results of the developed boundary element analysis are compared with those from the explicit solution and from the finite element analysis. It is observed that the boundary element analysis without internal cells results in some error because of its deficiency in handling the nonlinearity in local stress concentration. Therefore, a coupled analysis of boundary elements and finite elements, in which finite elements are used in the area of stress concentration, is developed. The coupled method is applied to a time dependent inelastic problem with semi-infinite boundaries. It results in reasonable solution compared with other methods where relatively higher degree of freedoms are employed. Thus, it is concluded that the combined analysis may be used for such problems in the effective manner.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.203-208
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• 2017

본 논문은 한글 자모 조합 임베딩을 이용하여 오타에 강건한 한국어 품사 태깅 시스템을 구축하는 방법에 대해 기술한다. 최근 딥 러닝 연구가 활발히 진행되면서 자질을 직접 추출해야 하는 기존의 기계학습 방법이 아닌, 스스로 자질을 찾아서 학습하는 딥 러닝 모델을 이용한 연구가 늘어나고 있다. 본 논문에서는 다양한 딥 러닝 모델 중에서 sequence labeling에 강점을 갖고 있는 bidirectional LSTM CRFs 모델을 사용하였다. 한국어 품사 태깅 문제에서 일반적으로 사용되는 음절 임베딩은 약간의 오타에도 품사 태깅 성능이 크게 하락하는 한계가 있었다. 따라서 이를 개선하기 위해 본 논문에서는 한글 자모 임베딩 값을 조합시킨 음절 임베딩 방식을 제안하였다. 강제로 오타를 발생시킨 테스트 집합에서 실험한 결과, 자모 조합 임베딩 기법이 word2vec 음절 임베딩 방식에 비해 형태소 분할은 0.9%, 품사 태깅은 3.5% 우수한 성능을 기록하였다.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.203-208
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• 2017

본 논문은 한글 자모 조합 임베딩을 이용하여 오타에 강건한 한국어 품사 태깅 시스템을 구축하는 방법에 대해 기술한다. 최근 딥 러닝 연구가 활발히 진행되면서 자질을 직접 추출해야 하는 기존의 기계학습 방법이 아닌, 스스로 자질을 찾아서 학습하는 딥 러닝 모델을 이용한 연구가 늘어나고 있다. 본 논문에서는 다양한 딥 러닝 모델 중에서 sequence labeling에 강점을 갖고 있는 bidirectional LSTM CRFs 모델을 사용하였다. 한국어 품사 태깅 문제에서 일반적으로 사용되는 음절 임베딩은 약간의 오타에도 품사 태깅 성능이 크게 하락하는 한계가 있었다. 따라서 이를 개선하기 위해 본 논문에서는 한글 자모 임베딩 값을 조합시킨 음절 임베딩 방식을 제안하였다. 강제로 오타를 발생시킨 테스트 집합에서 실험한 결과, 자모 조합 임베딩 기법이 word2vec 음절 임베딩 방식에 비해 형태소 분할은 0.9%, 품사 태깅은 3.5% 우수한 성능을 기록하였다.