• The Journal of Korean Philosophical History
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• no.32
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• pp.371-394
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• 2011

Buddhism have affected Korea traditional education very much. Sam Guk Yu Sa is a book which includes the public disposition grounded on world view of Buddhism. In the wide scope, the public disposition relates to their cultivating education. This paper reviewed cultivating education grounded on John Dewey "experience-learning" model about the Buddhistic public disposition appearing in Sam Guk Yu Sa. "Meaning-experience" as "adult-becoming" appearing in Sam Guk Yu Sa shows a strong characteristic of cultivating education when we see on a creative horizon in the Buddhistic world. Dewey-Deleuze's cultivating education which modernizes the theory of John Dewey meets at the place of the public disposition and three fables of Sam Guk Yu Sa grounded on the Buddhistic world. This could open possibility to interpret the cultivating theory of Korea traditional thought and western educational theory with interdigitation. Fables of Sam Guk Yu Sa dealt with growth and maturity of the public from Buddhist monk to folk wishes to achieve Bulgukto(佛國土; the land with Buddha) through the process of cultivating education which leads to "impulse-observation-knowledge-determination." In these series of process for "adult-becoming," life itself possesses characteristic of cultivating theory. In this respect, fables of Sam Guk Yu Sa shows Korea traditional cultivating theory and can be a role of a discourse book for cultivating educational theory which could relate to western educational theory.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.25-29
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• 2004

VoIP는 인터넷 프로토콜(IP)를 이용하여 음성을 데이터 packet처럼 전송하는 것을 의미한다. 최근 VoIP 기술의 도입으로 기존 망 성능 관리에 대한 관심이 높아지고 있다. 보다 원활한 기술 구현을 위해서는 VoIP 트래픽에 대한 체계적인 분석과 위험성 검증을 할 수 있는 도구가 필요하다. 또한 기존의 트래픽 시뮬레이션 기법에서 실제 망에서의 자기유사성을 적용한 사례가 적다는 것 또한 본 연구가 행하여진 동기이다. 본 연구에서는 자기유사성을 반영하여 소량의 샘플을 갖고 전체 VoIP 망 트래픽을 생성할 수 있는 방법론을 개발하고자 시도하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.687-696
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• 2014

This paper presents a semantic object extraction method using user's stroke input, color, and depth information. It is supposed that a semantically meaningful object is surrounded with a few strokes from a user, and has similar depths all over the object. In the proposed method, deciding the region of interest (ROI) is based on the stroke input, and the semantically meaningful object is extracted by using color and depth information. Specifically, the proposed method consists of two steps. The first step is over-segmentation inside the ROI using color and depth information. The second step is semantically meaningful object extraction where over-segmented regions are classified into the object region and the background region according to the depth of each region. In the over-segmentation step, we propose a new marker extraction method where there are two propositions, i.e. an adaptive thresholding scheme to maximize the number of the segmented regions and an adaptive weighting scheme for color and depth components in computation of the morphological gradients that is required in the marker extraction. In the semantically meaningful object extraction, we classify over-segmented regions into the object region and the background region in order of the boundary regions to the inner regions, the average depth of each region being compared to the average depth of all regions classified into the object region. In experimental results, we demonstrate that the proposed method yields reasonable object extraction results.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1586-1593
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• 2010

Vocabulary recognition error correction method has probabilistic pattern matting and dynamic pattern matting. In it's a sentences to based on key-word by semantic analysis. Therefore it has problem with key-word not semantic analysis for morphological changes shape. Recognition rate improve of vocabulary unrecognized reduced this paper is propose. In syllable restoration algorithm find out semantic of a phoneme recognized by a phoneme semantic analysis process. Using to sentences restoration that morphological analysis and morphological analysis. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.0% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.319-322
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• 2004

한글은 알파벳 문자처럼 소리를 바탕으로 한 표음문자이지만, 각 글자의 형태는 표의문자인 한자와 유사한 시각적인 효과를 제공한다. 본 연구에서는 자기공명 영상법을 이용하여 한국인이 한글문자와 그림을 인지할 경우 나타나는 신경망적 특성을 알아보았다. 그 결과. 한글과 그림 자극에 대하여 양반구 모두에서 후측두엽 부위의 활성화가 나타났다. 그러나, 전두엽과 측두엽 부분의 활성화는 오직 한글자극의 경우에만 관찰되었다. 좌반구 중전 두엽의 활성화는 음성 및 의미론적 처리와 관련되어 있다고 볼 수 있으며, 우반구 anterior cingulate 활성화는 언어 및 소리의 형성과 관계가 있다고 할 수 있다. 본 연구에서는 우반구 medial frontal 영역인 BA 8의 활성화가 관찰되었다 이 영역은 시각적으로 고차적인 비음성적 자극을 통제하거나 그와 유사한 시각공간적인 정보의 분석과 관련이 있다고 알려져 있다. 본 연구의 결과는 한글의 특성적인 형태가 특정 영역을 활성화시킨 것을 시사한다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.163-172
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• 2021

To specify a formal semantics for a programming language is to do a significant part for design, standardization and translation of it. The Python is popular and powerful, it is necessary to do research for a formal semantics to specify a static and dynamic semantics for Python clearly in order to design a similar language and do an efficient translation. This paper presents the Action Equation 2.0 that specifies a formal semantics for Python to change and update Action Equation. To measure the execution time for Python programs, we implemented the semantic structure specified in Action Equation 2.0 in Java, and prove through simulation that Action Equation 2.0 is a real semantic structure that can be implemented. The specified Action Equation 2.0 is compared to other descriptions, in terms of readability, modularity, extensibility, and flexibility and then we verified that Action Equation 2.0 is superior to other formal semantics.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.485-490
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• 2022

데이터 증강기법은 추가적인 데이터 구축 혹은 수집 행위 없이 원본 데이터셋의 양과 다양성을 증가시키는 방법이다. 데이터 증강기법은 규칙 기반부터 모델 기반 방법으로 발전하였으며, 최근에는 Masked Language Modeling (MLM)을 응용한 모델 기반 데이터 증강 연구가 활발히 진행되고 있다. 그러나 기존의 MLM 기반 데이터 증강 방법은 임의 대체 방식을 사용하여 문장 내 의미 변화 가능성이 큰 주요 토큰을 고려하지 않았으며 증강에 따른 레이블 교정방법이 제시되지 않았다는 한계점이 존재한다. 이러한 문제를 완화하기 위하여, 본 논문은 레이블을 고려할 수 있는 Re-labeling module이 추가된 MLM 기반 한국어 데이터 증강 방법론을 제안한다. 제안하는 방법론을 KLUE-STS 및 KLUE-NLI 평가셋을 활용하여 검증한 결과, 기존 MLM 방법론 대비 약 89% 적은 데이터 양으로도 baseline 성능을 1.22% 향상시킬 수 있었다. 또한 Gate Function 적용 여부 실험으로 제안 방법 Re-labeling module의 구조적 타당성을 검증하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.32-41
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• 2000

In this paper, we proposed a method which predict the verb by using the neural network in order to enhance communication rate in augmentative communication system for Korean language disorders. Each word is represented by an information vector according to syntax and semantics, and is positioned at the state space by being partitioned into various regions different from a dictionary-like lexicon. Conceptual similarity is realized through position in state space. When a symbol was pressed, we could find the word for the symbol at the position in the state space. In order to prevent verb prediction's redundancy according to input units, we predicted the verb after separating class using the neural network. In the result we can enhance $20\% communication rate in the restricted space

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.157-164
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• 2023

Specifying the semantic structure for functional interfaces and lambda expressions, which are the latest features of Java, can be referenced when designing similar functions in the future, and is also required in the process of standardizing or implementing an optimized translator. In this study, action equation 3.0 is newly proposed to express the static and dynamic semantic structure of functional interfaces and lambda expressions by modifying and upgrading the existing expressions to express the semantic structures of java functional interfaces and lambda expressions. Measure the execution time of java programs by implementing the semantic structure specified in action equation 3.0 in java, and prove that action equation 3.0 is a real semantic structure that can be implemented through simulation. The superiority of this action equation 3.0 is to be confirmed by comparing the action equation 3.0 specified in the four areas of readability, modularity, extensibility and flexibility with the existing representative semantic expression methods.