• Title/Summary/Keyword: 데이타 전처리

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A 3-D Visualization Method for Geographical Information based on Contour Lines (등고선을 이용한 자행정보의 3차원 시각화 기법)

  • Han, Jung-Kyu;Baek, Joong-Hwan;Hwang, Soo-Chan
    • Journal of Advanced Navigation Technology
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    • v.5 no.2
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    • pp.123-133
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    • 2001
  • The existing visualization methods using the satellite images or map images require complicated preprocessing stages and a large amount of visual data to represent the 3-D terrain. This paper presents a 3-D visualization method for geographical information, which enables automatic generation of 3-D terrain. It is generated based, on contour information obtained from a numerical map. This paper also introduces a method that resolves the three main problems needed to visualize 3-D terrain from contour lines such as correspondence, tiling, and branching. The virtual contour line is defined to extend a distorted contour line to have a similar shape to the corresponding contour line that is used, to generate 3-D surfaces. It helps that 3-D terrain is represented exactly and in detail.

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Efficient Processing of Transitive Closure Queries in Ontology using Graph Labeling (온톨로지에서의 그래프 레이블링을 이용한 효율적인 트랜지티브 클로저 질의 처리)

  • Kim Jongnam;Jung Junwon;Min Kyeung-Sub;Kim Hyoung-Joo
    • Journal of KIISE:Databases
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    • v.32 no.5
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    • pp.526-535
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    • 2005
  • Ontology is a methodology on describing specific concepts and their relationships, and it is being considered important more and more as semantic web and variety of knowledge management systems are being highlighted. Ontology uses the relationships among concerts to represent some concrete semantics of specific concept. When we want to get some useful information from ontology, we severely have to process the transitive relationships because most of relationships among concepts represent transitivity. Technically, it causes recursive calls to process such transitive closure queries with heavy costs. This paper describes the efficient technique for processing transitive closure queries in ontology. To the purpose of it, we examine some approaches of current systems for transitive closure queries, and propose a technique by graph labeling scheme. Basically, we assume large size of ontology, and then we show that our approach gives relative efficiency in processing of transitive closure, queries.

A Merging Algorithm with the Discrete Wavelet Transform to Extract Valid Speech-Sounds (이산 웨이브렛 변환을 이용한 유효 음성 추출을 위한 머징 알고리즘)

  • Kim, Jin-Ok;Hwang, Dae-Jun;Paek, Han-Wook;Chung, Chin-Hyun
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.3
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    • pp.289-294
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    • 2002
  • A valid speech-sound block can be classified to provide important information for speech recognition. The classification of the speech-sound block comes from the MRA(multi-resolution analysis) property of the DWT(discrete wavelet transform), which is used to reduce the computational time for the pre-processing of speech recognition. The merging algorithm is proposed to extract valid speech-sounds in terms of position and frequency range. It needs some numerical methods for an adaptive DWT implementation and performs unvoiced/voiced classification and denoising. Since the merging algorithm can decide the processing parameters relating to voices only and is independent of system noises, it is useful for extracting valid speech-sounds. The merging algorithm has an adaptive feature for arbitrary system noises and an excellent denoising SNR(signal-to-nolle ratio).

Pattern Classification Model using LVQ Optimized by Fuzzy Membership Function (퍼지 멤버쉽 함수로 최적화된 LVQ를 이용한 패턴 분류 모델)

  • Kim, Do-Tlyeon;Kang, Min-Kyeong;Cha, Eui-Young
    • Journal of KIISE:Software and Applications
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    • v.29 no.8
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    • pp.573-583
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    • 2002
  • Pattern recognition process is made up of the feature extraction in the pre-processing, the pattern clustering by training and the recognition process. This paper presents the F-LVQ (Fuzzy Learning Vector Quantization) pattern classification model which is optimized by the fuzzy membership function for the OCR(Optical Character Recognition) system. We trained 220 numeric patterns of 22 Hangul and English fonts and tested 4840 patterns whose forms are changed variously. As a result of this experiment, it is proved that the proposed model is more effective and robust than other typical LVQ models.

Design of Two Stage Amative Filters for Real time QRS Detection (실시간 ECG 분석을 위한 QRS 검출에 관한 연구 -2단 적응필터을 이용한-)

  • 이순혁;윤형로
    • Journal of Biomedical Engineering Research
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    • v.16 no.1
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    • pp.49-56
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    • 1995
  • This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter. The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively.

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A Signature Method for Efficient Preprocessing of XML Queries (XML 질의의 효율적인 전처리를 위한 시그너처 방법)

  • 정연돈;김종욱;김명호
    • Journal of KIISE:Databases
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    • v.30 no.5
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    • pp.532-539
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    • 2003
  • The paper proposes a pre-processing method for efficient processing of XML queries in information retrieval systems with a large amount of XML documents. For the pre-processing, we use a signature-based approach. In the conventional (flat document-based) information retrieval systems, user queries consist of keywords and boolean operators, and thus signatures are structured in a flat manner. However, in XML-based information retrieval systems, the user queries have the form of path query. Therefore, the flat signature cannot be effective for XML documents. In the paper, we propose a structured signature for XML documents. Through experiments, we evaluate the performance of the proposed method.

A Hybrid System of Wavelet Transformations and Neural Networks Using Genetic Algorithms: Applying to Chaotic Financial Markets (유전자알고리즘을 이용한 웨이블릿분석 및 인공신경망기법의 통합모형구축)

  • Shin, Taeksoo;Han, Ingoo
    • Proceedings of the Korea Database Society Conference
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    • 1999.06a
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    • pp.271-280
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    • 1999
  • 인공신경망을 시계열예측에 적용하는 경우에 고려되어야 할 문제중, 특히 모형에 적합한 입력변수의 생성이 중요시되고 있는데, 이러한 분야는 인공신경망의 모형생성과정에서 입력변수에 대한 전처리기법으로써 다양하게 제시되어 왔다. 가장 최근의 입력변수 전처리기법으로써 제시되고 있는 신호처리기법은 전통적 주기분할처리방법인 푸리에변환기법(Fourier transforms)을 비롯하여 이를 확장시킨 개념인 웨이블릿변환기법(wavelet transforms) 등으로 대별될 수 있다. 이는 기본적으로 시계열이 다수의 주기(cycle)들로 구성된 상이한 시계열들의 집합이라는 가정에서 출발하고 있다. 전통적으로 이러한 시계열은 전기 또는 전자공학에서 주파수영역분할, 즉 고주파 및 저주파수를 분할하기 위한 기법에 적용되어 왔다. 그러나, 최근에는 이러한 연구가 다양한 분야에 활발하게 응용되기 시작하였으며, 그 중의 대표적인 예가 바로 경영분야의 재무시계열에 대한 분석이다 전통적으로 재무시계열은 장, 단기의사결정을 가진 시장참여자들간의 거래특성이 시계열에 각기 달리 가격으로 반영되기 때문에 이러한 상이한 집단들의 고유한 거래움직임으로 말미암아 예를 들어, 주식시장이 프랙탈구조를 가지고 있다고 보기도 한다. 이처럼 재무시계열은 다양한 사회현상의 집합체라고 볼 수 있으며, 그만큼 예측모형을 구축하는데 어려움이 따른다. 본 연구는 이러한 시계열의 주기적 특성에 기반을 둔 신호처리분석으로서 기존의 시계열로부터 노이즈를 줄여 주면서 보다 의미 있는 정보로 변환시켜 줄 수 있는 웨이블릿분석 방법론을 새로운 필터링기법으로 사용하여 현재 많은 연구가 진행되고 있는 인공신경망과의 모형결합을 통해 기존연구와는 다른 새로운 통합예측방법론을 제시하고자 한다. 본 연구에서 제시하는 통합방법론은 크게 2단계 과정을 거쳐 예측모형으로 완성이 된다. 즉, 1차 모형단계에서 원시 재무시계열은 먼저 웨이블릿분석을 통해서 노이즈가 필터링 되는 동시에, 과거 재무시계열의 프랙탈 구조, 즉 비선형적인 움직임을 보다 잘 반영시켜 주는 다차원 주기요소를 가지는 시계열로 분해, 생성되며, 이렇게 주기에 따라 장단기로 분할된 시계열들은 2차 모형단계에서 신경망의 새로운 입력변수로서 사용되어 최종적인 인공 신경망모델을 구축하는 데 반영된다.

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Code Generation for Integrity Constraint Check in Objectivity/C++ (Objectivity/C++에서 무결성 제약조건 확인을 위한 코드 생성)

  • Kim, In-Tae;Kim, Gi-Chang;Yu, Sang-Bong;Cha, Sang-Gyun
    • Journal of KIISE:Computing Practices and Letters
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    • v.5 no.4
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    • pp.416-425
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    • 1999
  • 복잡한 무결성 제약 조건을 효율적으로 확인하기 위해 제약 조건들을 룰 베이스(rule base)에 저장하고 별도의 룰 관리 시스템과 제약 조건 관리 시스템을 통해 제약 조건을 확인하는 기법이 많은 연구자들에 의해 연구되고 발표되었다. 그러나 제약 조건 관리 시스템이 실행시간에 응용 프로그램을 항상 모니터링하고 있다가 데이타의 수정이 요청될 때마다 개입하여 프로세스를 중단시키고 관련 제약 조건을 확인하는 기존의 방법들은 처리 시간의 지연을 피할 수 없다. 본 논문은 컴파일 시간에 제약 조건 확인 코드를 응용 프로그램에 미리 삽입할 것을 제안한다. 응용 프로그램 자체 내에 제약 조건 확인 코드가 삽입되기 때문에 실행 시간에 다른 시스템의 제어를 받지 않고 직접 제약 조건의 확인 및 데이타베이스의 접근이 가능해져서 처리 시간의 지연을 피할 수 있을 것이다. 이를 위해 어떤 구문이 제약 조건의 확인을 유발하는 지를 추적하였고, 컴파일러가 그러한 구문을 어떻게 전처리 과정에서 검색하는지 그리고 그러한 구문마다 어떻게 해당 제약 조건 확인 코드를 삽입할 수 있는 지를 객체지향1) 데이타베이스 언어인 Objectivity/C++에 대해 gcc의 YACC 코드를 변경함으로써 보여 주었다.Abstract To cope with the complexity of handling integrity constraints, numerous researchers have suggested to use a rule-based system, where integrity constraints are expressed as rules and stored in a rule base. A rule manager and an integrity constraint manager cooperate to check the integrity constraints efficiently. In this approach, however, the integrity constraint manager has to monitor the activity of an application program constantly to catch any database operation. For each database operation, it has to check relevant rules with the help of the rule manager, resulting in considerable delays in database access. We propose to insert the constraints checking code in the application program directly at compile time. With constraints checking code inserted, the application program can check integrity constraints by itself without the intervention of the integrity constraint manager. We investigate what kind of statements require the checking of constraints, show how the compiler can detect those statements, and show how constraints checking code can be inserted into the program, by modifying the GCC YACC file for Objectivity/C++, an object-oriented database programming language.

The Recognition of Printed Korean Characters by a Neural Network (신경회로망을 이용한 인쇄체 한글 문자의 인식)

  • Kim, Sang-Woo;Jeon, Yun-Ho;Choi, Chong-Ho
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.2
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    • pp.65-72
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    • 1990
  • The potential of neural networks for the recognition of the printed Korean characters is examined. In spite of good classification capability of neural networks, it is difficult to train a neural network to recognize Korean characters. The difficulty is due to a large number of Korean characters, the similarities among the characters, and the large number of data from the character images. To reduce the input image data, DC components are extracted from each input images. These preprocessed data are used as input to the neural network. The output nodes are composed to represent the characteristics of Korean characters. A MLP (multilayer perceptron) with one hidden layer was trained with a modified BEP algorithm, This method gives good recognition rate for the standard positioned characters of more than 2,300. The result shows that neural networks are well suited for the recognition of printed Korean characters.

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Utilization of Syllabic Nuclei Location in Korean Speech Segmentation into Phonemic Units (음절핵의 위치정보를 이용한 우리말의 음소경계 추출)

  • 신옥근
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.5
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    • pp.13-19
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    • 2000
  • The blind segmentation method, which segments input speech data into recognition unit without any prior knowledge, plays an important role in continuous speech recognition system and corpus generation. As no prior knowledge is required, this method is rather simple to implement, but in general, it suffers from bad performance when compared to the knowledge-based segmentation method. In this paper, we introduce a method to improve the performance of a blind segmentation of Korean continuous speech by postprocessing the segment boundaries obtained from the blind segmentation. In the preprocessing stage, the candidate boundaries are extracted by a clustering technique based on the GLR(generalized likelihood ratio) distance measure. In the postprocessing stage, the final phoneme boundaries are selected from the candidates by utilizing a simple a priori knowledge on the syllabic structure of Korean, i.e., the maximum number of phonemes between any consecutive nuclei is limited. The experimental result was rather promising : the proposed method yields 25% reduction of insertion error rate compared that of the blind segmentation alone.

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