• Journal of Oral Medicine and Pain
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• v.17 no.2
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• pp.109-117
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• 1992

저출력레이저는 인체조직에 biostimulation effects를 가지므로 구강주위에 발생하는 여려가지 질병에 대한 저출력레이저광의 효과에 관하여 많은 연구가 시도되고 있으며 또한 치료에 응용되고 있다. 감염창상에 저출력레이저 조사시 조직치유의 기전이 세균 성장에 의한 조직손상보다 주위 정상조직의 biostimulation effects가 우세하기 때문이라는 가설을 확인하고저 본 연구를 시행하였다. 백서 7마리를 레이저 조사군과 대조군으로 나누어 감염창상의 면적차이를 비교하여 다음고 같은 결론을 얻었다. 1. 저출력레이저 조사군에서 창상수축율이 현저히 높았다. 2. 부종의 빈도는 저출력레이저 조사시 뚜렷하게 감소하였다. 위의 사실로 보아 저출력레이저 조사시 감염창상의 치유촉진은 주위 정상조직의 biostimulation effect가 세균증식에 의한 조직의 손상보다 우세하기 때문이라는 가설을 확인할 수 있었다.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.402-410
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• 2020

It is very important for Academic purpose Korean leaner to understand main ideas and overall context of texts. In order to understand the overall context and mail ideas of text, learners need output task, ways to perform what they are learning, such as retelling. That would help them to realize that there is a gap between what they have understood and what they can actually speak or write. These out activities help learners comprehend the text more efficiently, while at the same time raising their confidence level. The purpose of this study was to develop an education plan to improve reading comprehension ability by using retelling activity. To achieve the purpose of the study, retelling activity, which makes it easier to take an integrated approach to language function and is considered to be relatively effective, was utilized because of the characteristics of retelling activity education instead of teacher-centered education methods.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.1-10
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• 2005

This paper presents a map matching method using multiple hypothesis technique(MHT) to identify the road that a land vehicle is located on. To realize a map matching method using MHT, Pseudo-measurements are generated utilizing adjacent roads of GPS/DR position and the MHT is reformulated as a single target problem. Since pseudo-measurements are generated using digital map, topological properties such as road connection, direction, and road facility information are considered in calculating probabilities of hypotheses. In order to improve the map matching performance under when bias errors exist in digital road map data, a Kalman filter is employed to estimate the biases. Field experimental results show that the proposed map matching method provides the consistent performance even in complex downtown areas, overpass/underpass areas, and in the areas where roads are adjacent in parallel.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.270-277
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• 2002

Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.13-21
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• 2023

This paper proposes a method of automatically generating a model through a machine learning technique by setting a hypothetical model in the form of a gray box or black box with unknown parameters, when the big data of the actual system is given. We implements the proposed framework and conducts experiments to find an appropriate model among various hypothesis models and compares the cost and fitness of them. As a result we find that the proposed framework works well with continuous systems that could be modeled with ordinary differential equation. This technique is expected to be used well for the purpose of automatically updating the consistency of the digital twin model or predicting the output for new inputs using recently generated big data.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.419-422
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• 2023

자연어 추론은 전제 문장과 가설 문장의 관계를 함의, 중립, 모순으로 분류하는 자연어 처리 태스크이다. 최근 여러 자연어 처리 태스크에서 딥러닝 모델을 이용하는 방법이 우수한 성능을 보이고 있지만, 이는 미세 조정과정에 드는 비용이 많다는 점과 모델 출력의 근거, 과정을 사람이 이해하기 어려운 한계가 있다. 이러한 이유로 최근에는 소량의 입력, 출력 예시를 포함한 프롬프트를 이용한 방법론과 모델 출력에 대한 근거를 생성, 활용하는 방법에 관한 많은 연구가 진행되고 있다. 본 논문에서는 퓨샷 학습 환경의 한국어 자연어 추론 태스크를 위한 세 가지 프롬프트 방법과 이들을 조합하여 적용하는 방법을 제안한다. 이를 통해 '해석 가능성'과 자연어 추론 성능을 모두 향상시킬 수 있음을 보인다.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.375-382
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• 2006

This paper is about how to identify emotional information and how to detect a specific emotion from speech signals. For emotion identification and detection task. we use long-term acoustic feature parameters and select the optimal Parameters using the feature selection technique based on F-score. We transform the conventional SVM into probabilistic output SVM for our emotion identification and detection system. In this paper we propose three approximation methods for log-likelihoods in a hypothesis test and compare the performance of those three methods. Experimental results using the SUSAS database showed the effectiveness of both feature selection and Probabilistic output SVM in the emotion identification task. The proposed methods could detect anger emotion with 91.3% correctness.

• Cross-Cultural Studies
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• v.37
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• pp.287-307
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• 2014

The purpose of this paper is to introduce a new and effective classroom speaking activity helping student's communication in real situation. It will be one of useful teaching techniques for teachers because it can be used with other various types of speaking activities together. The activity is designed by the researcher, and named as the Partner's Speech Reconstitution(PSR) in this paper. In chapter 2, Noticing and Output hypothesis which is the theoretic basis of the PSR will be described and the chapter 3 will explain activity methods and examples of the PSR, and then describe its merits and demerits. The researcher applied and practiced the PSR in the speaking class for international students in the K university for three semesters. This paper systematically introduces its organized activity. It helped learners elicit speaking performance of students who avoided talking in the speaking class, made the students concentrate in speaking activity, and helped the learners to talk sufficiently by inducing each student to reconstitute partner's speech production.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.4
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• pp.1-10
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• 1992

Since the structural system of a prestressed concrete bridge erected by Incremental Launching Method is varying continuosly during construction, the main girder bears alternating stress resultants different from those under a service load condition. The magnitude of these stress resultants depends on span lengths, nose length and stiffness ratios between girder and nose. A parametric study is performed for various span lengths, nose lengths and stiffness ratios. In order to analyze structural systems varying at every launching step two programs are developed; a pre-processor which automatically produces a data file for each stage and a main-processor which can summarize the results of all stages. From the results, the relationships between optimum nose length and stiffness ratio are proposed for various span lengths.

• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.223-230
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• 1994

본 한글꼴은 음절 및 음소의 가시성을 높이고자 한글 음소의 이중 가로선형 배열을 통한 밀도 분산형 한글꼴과 음소 나열형 한글꼴 등의 새로운 한글꼴의 다양한 표현의 실험 연구이다. 일도 분산형 한글꼴은 새로운 음소형 한글코드(닿소리, 홑소리, 받침 조합형)와 서로 대응하드록 일원화 한글꼴로 한글 및 옛 한글의 음소 조합형의 입.출력이 가능하다. 이러한 시도는 1바이트 이내에서 현대한글 및 옛한글을 구현하며, 이는 한글의 구현원리에 따른 음소형 코드체계의 실현 가능성으로 한글 코드체계의 최적화에 대한 새로운 가설을 제시 한다.