• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.580-587
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• 2000

In this paper, we present a design method of a digital filter converting humming voice melody into MIDI data and a method of adapting it to a distributed multimedia I/O server. MuX uses device-independent DLMs(Dynamic Linking Module) for the inteliace with various I/O devices, and has wave-form audio DLM and MIDI DLM for audio interfaces. In order to expand the audio device interfacing ability of MuX system, we have designed and implemented a filter transforming human voice into MIDI messages. As the methods to input MIDI data are expanded to human voice in addition to MIDI files and MIDI instrument, someone who is not good at playing instruments can also generate the MIDI data, which enables our media interfaces to be used in various applications.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.97-111
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• 2008

Commercial data mining tools basically support binary attributes only in mining association rules, that is, they can mine binary association rules only. In general, however. transaction databases contain not only binary attributes but also quantitative attributes. Thus, in this paper we propose a systematic approach to mine quantitative association rules---association rules which contain quantitative attributes---using commercial mining tools. To achieve this goal, we first propose an overall working framework that mines quantitative association rules based on commercial mining tools. The proposed framework consists of two steps: 1) a pre-processing step which converts quantitative attributes into binary attributes and 2) a post-processing step which reconverts binary association rules into quantitative association rules. As the pre-processing step, we present the concept of domain partition, and based on the domain partition, we formally redefine the previous bipartition and multi-partition techniques, which are mean-based or median-based techniques for bipartition, and are equi-width or equi-depth techniques for multi-partition. These previous partition techniques, however, have the problem of not considering distribution characteristics of attribute values. To solve this problem, in this paper we propose an intuitive partition technique, named standard deviation minimization. In our standard deviation minimization, adjacent attributes are included in the same partition if the change of their standard deviations is small, but they are divided into different partitions if the change is large. We also propose the post-processing step that integrates binary association rules and reconverts them into the corresponding quantitative rules. Through extensive experiments, we argue that our framework works correctly, and we show that our standard deviation minimization is superior to other partition techniques. According to these results, we believe that our framework is practically applicable for naive users to mine quantitative association rules using commercial data mining tools.

• Proceedings of the Korean Society for Information Management Conference
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• 1998.08a
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• pp.201-204
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• 1998

인터넷의 자원에 접근하기 위해서는 그 정보를 조직화할 필요성이 있으며, 조직화된 자료들은 디지털화되어 서비스될 수 있도록 기술이 발전하고 있다. 따라서, 현존하는 도서관의 편목 기술과 절차를 응용하여 인터넷 자원에 적용한 OCLC 매뉴얼과 네트워크상의 자원에 대한 목록을 메타데이타로 기술한 DUBLIN core 기술법을 비교분석하여, MARC 포맷으로의 변환을 살펴 본 바, 더블린 코아 형태로 제공되는 메타데이타 요소는 MARC포맷의 각 필드로 변환 할 수 있어야 하며, 더블린 코아와 같은 간략형 서지레코드의 요소를 더욱 개발해야 한다. 또한, 여러 유형의 메타데이타 통합에 대한 방법으로 MARC에 대한 수정 및 새로운 필드의 마련이 필요하며, 표준기술규칙의 마련으로 정확하고 대량의 데이터를 구축하며, 특히 이러한 기술법을 익힌 전문가들의 등장이 필요할 것이다.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.42-55
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• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• Progress in Medical Physics
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• v.5 no.2
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• pp.27-34
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• 1994

In this study, we developed E.C.G telemetry system by using a digital communication method. This system is composed of a number of Ambulatory Telemetry System(ATS)'s that use for the same frequency and one center monitoring system(CMS) utilized the personal computer. The purpose of the ATS is, Therefore, to present for acqusition ECG data and transmitting to CMS. The ATS hardware is based on one chip microprocessor (8096) included A/D convert, ECG pre amplifier, ID-decoder, TRX Gateway and FM TRX module. Using the PC can be convinet to processing and deposite for long terms continued patient data.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.43-48
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• 1994

본 논문은 반복 수축 변환의 프랙탈(fractal) 이론에 근거한 심전도 데이터 압축에 관한 연구이다. 심전도 데이터에 반복 함수계(Iterated Function System : IFS) 모델을 적용하여 신호 자체의 자기 유사성(self-similarity)을 반복 수축 변환으로 표현하고, 그 매개변수만을 저장한다. 재구성시는 변환 매개변수를 반복 적용하여 원래의 신호에 근사되어지는 값을 얻게 된다. 심전도 데이타는 부분적으로 자기 유사성을 갖는다고 보고, 부분 자기-유사 프랙탈 모델(piecewise self-affine fractal model)로 표현될 수 있다. 이 모델은 신호를 특정 구간들로 나누어 각 구간들에 대해 최적 프랙탈 보간(fractal interpolation)을 구하고 그 중 오차가 가장 작은 매개변수만을 추출하여 저장한다. 이 방법을 심전도 데이타에 적용한 결과 특정 압축율에 대해 아주 적은 재생오차 (percent root-mean-square difference : PRD)를 얻을 수 있었다.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.789-794
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• 2005

LDA (Linear Discriminant Analysis) provides the projection that discriminates the data well, and shows a very good performance for face recognition. However, since LDA provides only one transformation matrix over whole data, it is not sufficient to discriminate the complex data consisting of many classes like honan faces. To overcome this weakness, we propose a new face recognition method, called LDA mixture model, that the set of alf classes are partitioned into several clusters and we get a transformation matrix for each cluster. This detailed representation will improve the classification performance greatly. In the simulation of face recognition, LDA mixture model outperforms PCA, LDA, and PCA mixture model in terms of classification performance.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.634-644
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• 1995

In this paper, we propose a mechanism to transform more effective and semantically equivalent queries by using appropriately represented three kinds of knowledge. Also we proposed a mechanism which transforms partially omitted components or expressions into complete queries so that users can use more simple queries. The knowledges used to transform and optimize are semantic, structural and domain knowledge. Semantic knowledge includes semantic integrity constraints and domain integrity constraints. Structural knowledge represents physical relationship between relations. And domain knowledge maintains the domain information of attributes. The proposed system optimizes to more effective queries by eliminating/adding/replacing unnecessary or redundant restrictions/joins.

• Proceedings of the Korea Database Society Conference
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• 2001.06a
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• pp.303-310
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• 2001

XML은 웹에서 데이터 교환을 위한 마크업 언어로 반-구조화된 정보나 구조화된 정보를 교환하고 저장할 수 있으며, 표준언어로 채택되어 가고 있고, 강력한 표현력을 가지고 있기 때문에 다양한 애플리케이션을 가능하게 한다. 문서와 객체가 구조화 될 수 있는 방법을 제공하는 XML은 계층적 구조로 이루어진다. ORDB에서는 스키마 객체들이 계층적 구조로 구성되어 하나의 큰 객체를 이룬다. XML과 ORDB 사이에 단순한 XML 문서는 직접 변환이 가능하나 복잡한 XML 문서를 다룰 때는 객체 기반 변환 방법으로 처리되어야 한다. 따라서 본 논문에서는 XML DTD를 객체로 변환하고 변환된 객체를 ORDB 스키마로 변환하는 방법에 대하여 연구하였다.

• 한국공간정보시스템학회:학술대회논문집
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• 2000.06a
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• pp.109-122
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• 2000

기존의 통합 시스템은 이미 구축된 자윈을 재활용하여 데이타의 구축비용을 줄이고자 하는 의도에서 연구되었다. 특히 GIS에서는 공간 데이타의 규모가 방대하므로 그 구축비용이 더욱 증가한다. 이로 인해 공간 데이타를 위한 통합 시스템의 필요성이 대두되다. 최근 웹의 사용자 수와 그 응용의 수가 증가함에 따라 웹에서의 공간 데이타를 이용한 응용의 필요성이 승가하고 있다. 이에 따라 웹 환경에서 분산된 공간 데이타의 통합 시스템이 요구된다. 기존의 미디에이터(Mediator)를 사용한 통합에 비하여 웹을 기반한 공간 데이타의 통합은 웹의 환경적 특성과 공간 데이타의 크기와 형태 등을 고려해야 한다. 본 논문에서는 OGC(OpenGIS Consortium)의 웹 매핑 기술인 WMT(Web Mapping Testbed)의 중첩 맵 서버 (Cascading Map Server)를 사용하여 공간 데이타를 통합한다. 통합 과정에서 요구되는 표준화된 데이타 모델과 인터페이스는 OGC가 최근 제안한 GML(Geography Markup Language)과 웹 맵 서버 인터페이스를 이용한다. 본 논문은 XML의 XLink와 XPointer의 개념을 가진 융합 서비스(Fusion Service)기법을 중첩 맵 서버에 도입한 융합 맵 서버(Fusion Map Server)를 제안한다. 이러한 통합 방식은 데이터 사이의 관계성을 고려한 링킹 기반 통합이므로 통합 응용의 복잡성을 줄일 수 있을 뿐만 아니라 물리적 변환 등에서 생성되는 연산 비용을 줄일 수 있는 장점이 있다.