• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.618-623
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• 2011

This paper proposes a novel method to discriminate meaningful tables from decorative one using a composite kernel for handling structural information of tables. In this paper, structural information of a table is extracted with two types of parse trees: context tree and table tree. A context tree contains structural information around a table, while a table tree presents structural information within a table. A composite kernel is proposed to efficiently handle these two types of trees based on a parse tree kernel. The support vector machines with the proposed kernel dised kuish meaningful tables from the decorative ones with rich structural information.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.171-178
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• 2022

In this paper, we propose a classification method according to the type and characteristics of stablecoins for risk analysis, and analyze the risk factors of each stablecoin based on this classification. First, this paper explains the technologies and ecosystem of blockchain and decentralized finance(DeFi) to understand stablecoins. In addition, the operation principle of the major stablecoins currently released and used is explained for each proposed classification type. Based on this, the risk type and risk factors of each stablecoin are derived. The risk types proposed in this paper are classified as defegging, liquidation, and exploit, and the risk factors are classified as depegging due to reliability of operator, depegging due to reliability of algorithm, depegging due to failure of algorithm, liquidation due to high volatilty and oracle attack. Based on the proposed classification, we analyze the risk factors of major stablecoins currently circulating in the crypto market.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.682-684
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• 2002

최근 여러 논문에서 실 데이터 종속을 제거하기 위하여 결과 값 예상 기법을 제안하였다. 결과 값 예상 기법 중 혼합형 결과 값 예측기는 다양한 패턴을 갖는 명령어를 모두 예측함으로써 높은 예상 정확도를 얻을 수 있지만 하나의 명령어가 여러 개의 예측기 테이블에 중복 저장되어 높은 하드웨어 비용을 요구한다는 단점이 있다. 본 논문에서는 이러한 단점을 극복하기 위하여 프로파일링으로 얻어진 정적 분류 정보를 사용하여, 명령어률 예상 정확도가 높은 예측기에만 할당하여 예상 테이블 크기를 감소 시켰다. 또한 동적으로 적절한 예측기를 선택하도록 함으로써 예상 정확도를 더욱 향상 시켰다. 본 논문에서는 SPECint95 벤치마크 프로그램에 대해 SimpleScalar/PISA 3.0 툴셋을 사용하여 실험하였다. 정적-동적 분류 정보를 모두 사용하였을 경우 87.9%, VHT 크기를 4K로 축소한 경우 87.5%로 비슷한 예상정확도를 얻으면서 예상 테이블의 크기는 50%로 감소하였다. 또한 실행 패턴의 유형 비율에 따라 각 예측기의 VHT를 구성한 경우 예상 테이블 크기를 25%로 줄일 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.295-297
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• 2012

현재 법률과 관련된 문서들은 변경 사항 에 대한 공표와 기록의 중요성을 가지고 있다. 따라서 변경사항을 자동으로 인지하고 공표할 수 있는 자동화 시스템에 대한 관심과 연구가 진행되고 있다. 그러나 대부분의 문서들은 복잡한 구조이기 때문에 자동화에 어려움이 많다. 이로 인해 복잡한 구조의 문서를 자동으로 판별할 수 있는 방법에 관한 관심이 증대되고 있다. 현재 국내외에서는 전자 문서 파일의 텍스트 및 테이블을 판별해서 분류 하는 자동화에 대한 연구가 진행되고 있다. 하지만 이전 연구에서는 호목단 구조를 갖는 계층적인 테이블을 판별하지 않는다. 그래서 본 논문에서는 호목단을 정의하고, 테이블의 호목단 구조를 패턴 별로 분류 하며, 테이블의 호목단 구조 판별 방법을 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.88-90
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• 2021

This paper introduces a method for extracting subtitles from lecture videos through a Korean morpheme analyzer and classifying video categories according to the extracted morpheme information. In some cases incorrect information is entered due to human error and reflected in the characteristics of the items, affecting the accuracy of the recommendation system. To prevent this, we generate a keyword table for each category using morpheme information extracted from pre-classified videos, and compare the similarity of morpheme in each category keyword table to classify categories of Lecture videos using the most similar keyword table. These human intervention reduction systems directly classify videos and aim to increase the accuracy of the system.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.84-91
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• 2007

Recently, the researches based on vision about user attention and action awareness are being pushed actively for human computer interaction. Among them, various applications of tabletop display system are developed more in accordance with touch sensing technique, co-located and collaborative work. Formerly, although supported only one user, support multi-user at present. Therefore, collaborative work and interaction of four elements (human, computer, displayed objects, physical objects) that is ultimate goal of tabletop display are realizable. Generally, tabletop display system designs according to four key aspects. 1)multi-touch interaction using bare hands. 2)implementation of collaborative work, simultaneous user interaction. 3)direct touch interaction. 4)use of physical objects as an interaction tool. In this paper, we describe a critical analysis of the state-of-the-art in advanced multi-touch sensing techniques for tabletop display system according to the four methods: vision based method, non-vision based method, top-down projection system and rear projection system. And we also discuss some problems and practical applications in the research field.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.709-716
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• 2005

QoS is an important requirement of the FTTH (Fiber To The Home) subscriber in access network using E-PON (Ethernet Passive Optical Network). In this research, we describe the structure of the access network and propose a bandwidth guarantee scheme for subscriber and service according to the requirements of the subscriber, service and system. This scheme uses two kinds of the classification table, which are called 'service classification table' and 'subscriber classification table.' Using the classification table, we can identify the flow of the subscriber and service. Also, we compute the number of hash table entry to minimize the loss ratio of flows using the M/G/k/k queueing model. Finally, we apply the DRR scheduling through virtual queueing per subscriber instead of the aggregated class.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.616-621
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• 2006

Recently, the researches based on vision about user attention and action awareness are being pushed actively for human computer interaction. Among them, various applications of tabletop display system are developed more in accordance with touch sensing technique, co-located and collaborative work. Formerly, although supported only one user, support multi-user at present. Therefore, collaborative work and interaction of four elements (human, computer, displayed objects, physical objects) that is ultimate goal of tabletop display are realizable. Generally, tabletop display system designs according to four key aspects. 1)multi-touch interaction using bare hands. 2)implementation of collaborative work, simultaneous user interaction. 3)direct touch interaction. 4)use of physical objects as an interaction tool. In this paper, we describe a critical analysis of the state-of-the-art in advanced multi-touch sensing techniques for tabletop display system according to the four methods: vision based method, non-vision based method, top-down projection system and rear projection system. And we also discuss some problems and practical applications in the research field.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.115-117
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• 2004

롤업과 드릴다운은 다차원 데이터 분석을 위한 주요 연산으로, 각 차원에 정의된 계층구조를 통해 상세 데이터로부터 점차적으로 되는 정보를 분석가에게 제공한다. 이러한 연산 속도를 고속화하기 위해 OLAP 시스템은 사전에 집계 테이블들을 생성해 놓는다. 각 차원은 다중 계층구조를 가질 수도 있으며, 이런 경우 집계 테이블들을 모두 생성하게 되면 데이터 폭발 현상이 발생하게 된다. 본 연구에서는 다중계층 구조를 분류하고, 집계 테이블과 데이터 큐브의 크기를 계산하는 모델을 정립하였다. 이를 통해 분석가는 다중 계층구조에 따른 큐브 크기를 미리 예측할 수 있으며 계층 구조의 모양과 개수를 변경하여 데이터의 양을 조절할 수 있다.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.383-387
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• 2012

Development of automated document management system specified for scanned invoice images suffers from rigorous accuracy requirements for extraction of monetary data, which necessiate automatic validation on the extracted values for a generative invoice table model. Use of certain internal constraints such as "amount = unit price times quantity" is typical implementation. In this paper, we propose a noble invoice information extraction model with improved auto-validation method by utilizing table header detection and column classification.