• 한국가시화정보학회:학술대회논문집
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• 한국가시화정보학회 2006년도 추계학술대회 논문집
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• pp.73-77
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• 2006

Flow rate measurement is one of the difficult problems in the industrial applications. Especially, flow rate in a partially filled pipeline is affected by many parameters such as water level, channel slop, etc. In the present study, prior to the development of a flowmeter, the flow characteristics has been investigated by particle image velocimetry (PIV) measurements. Three-dimensional velocity distributions were obtained from sectional measurements of velocity profiles according to the water level. As a result, it is found that there is no similarity in the velocity profile when the lateral position is changed. In addition, the maximum velocity does not always occur on the free surface. It depends on the water level. In the aspect of flow rate measurement, the previous calculus based upon point measurement techniques is proved to be inaccurate because of the lack of whole flow information.

• 한국콘텐츠학회논문지
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• 제11권12호
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• pp.52-59
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• 2011

이 논문에서는 시퀀스 데이터베이스에서 효과적인 유사 검색을 지원하기 위한 색인 기법을 제안한다. 제안하는 색인 기법에서는 데이터 시퀀스에 대한 필터링 효과를 얻기 위해, 최소 DTW 거리를 새롭게 제안한다. 최소 DTW 거리는 유사한 데이터 시퀀스 그룹과 질의 시퀀스 사이의 최소거리를 측정하는 방법이다. 최소 DTW 거리는 계층적인 색인 구조를 통해서 시퀀스 데이터베이스를 필터링하면서 유사도 검색을 수행할 수 있도록 한다. 마지막으로, 실험을 통해서 제안하는 방법의 우수성을 입증한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.607-610
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• 1998

The major objectives of speech coding include high compression ratio for transmission in the band limited channel, high synthesized speech quality in terms of the intelligibility and the naturalness and fast processing speed. In general, speech coding methods are classified into the following three categories: the wavelform coding, the source coding and the hybird coding. In this paper, we proposed a new waveform coding method using PSOLA(pitch-synchronous overlap add) technique. First, we fixed one basic waveform per pitch and measured the formant similarity between basic and neighbor waveform. Second, if the similairy satisfied threshold values, we compress the neighbor waveform per pitch and then store or transmit. When the comparession is about 45%, we obtained about 4 in MOS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.206-209
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• 2002

This paper proposes a fractal dimension method for measurement of degree of similarity between prototype pattern and input pattern at ART1 (Adaptive Resonance Theory 1) neural network. In order to confirm the validity of proposed method, comparison of the performance has made between the conventional method and the proposed method through simulation. The results show that the proposed method has considerably improved the performance.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 가을 학술발표논문집 Vol.34 No.2 (C)
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• pp.29-34
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• 2007

월드와이드웹에서의 정보를 재사용, 공유할 수 있도록 기준을 제시한 XML은 많은 곳에서 사용 중에 있으며, 널리 확산되고 있다. 사용자 정의태그를 이용한 XML의 특징은, 같은 도메인의 문서라도 사랑의 인식이 아닌 컴퓨터와 같은 기계적으로는 다르게 인식될 수 있다는 문제점을 드러내기도 한다. 본 논문에서는 이러한 문제점을 해결하고자 시소러스와 온톨로지 등을 이용해 XML 문서간 유사도를 측정하는 방법을 제시하며 이를 바탕으로 제작한 프로그램인 #XML Similarity Calculation# 를 이용하여 제시한 방법이 타당하다는 것을 증명하게 된다. 또한 주어진 예시자료를 가지고 이 프로그램의 성능평가를 통해 정확성과 효율성을 평가하고 앞으로의 연구방향을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• 대한전기학회논문지:전력기술부문A
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• 제48권3호
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• pp.342-349
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• 1999

The metric defined on the domain deformation space better measures the similarity between bounded and continuous signals for the purpose of classification via the metric distances between signals. In this paper, a modified domain deformation theory is introduced for one-dimensional signal classification. A new metric defined on a modified domain deformation for measuring the distance between signals is employed. By introducing a newly defined metric space via the newly defined Integra-Normalizer, the assumption that domain deformation is applicable only to continuous signals is removed such that any kind of integrable signal can be classified. The metric on the modified domain deformation has an advantage over the $L^2$ metric as well as the previously introduced domain deformation does.

• International Journal of Contents
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• 제9권2호
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• pp.1-7
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• 2013

This paper proposes an efficient matching algorithm based on ASIFT (Affine Scale-Invariant Feature Transform) which is fully invariant to affine transformation. In our approach, we proposed a method of reducing similar measure matching cost and the number of outliers. First, we combined the Manhattan and Chessboard metrics replacing the Euclidean metric by a linear combination for measuring the similarity of keypoints. These two metrics are simple but really efficient. Using our method the computation time for matching step was saved and also the number of correct matches was increased. By applying an Optimized Random Sampling Algorithm (ORSA), we can remove most of the outlier matches to make the result meaningful. This method was experimented on various combinations of affine transform. The experimental result shows that our method is superior to SIFT and ASIFT.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.36-39
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• 2019

데이터 마이닝에서 클러스터링은 서로 유사한 특징을 갖는 데이터들을 동일한 클래스로 분류하는 방법이다. 클러스터링에는 다양한 방법이 존재하지만 대표적으로 집합으로 표현된 데이터들의 유사도를 측정하기 위해서는 자카드 유사도(Jaccard Similarity)를 이용한다. 자카드 유사도는 서로 다른 집합 간의 공통된 부분을 상대적으로 평가하여 유사도를 측정하는 방법이다. 그러나 최근에는 데이터를 저장할 수 있는 기술과 매체의 발전으로 표현할 수 있는 데이터의 영역과 범위는 발전되고 있기 때문에 많은 연산과 시간의 비용이 발생하게 된다. 이를 해결하기 위해서 두 데이터의 표본의 유사도를 통해 실제 데이터들의 유사도를 추정할 수 있는 Min-Hash 가 제안되었다. 본 논문에서는 이를 활용하여 집합의 영역을 다중 집합(Multiset)으로 확장하여 중복되는 값을 가질 수 있는 두 데이터 간의 유사도를 효율적으로 추정할 수 있는 Min-Max Hash 를 제안한다.

• 한국해양공학회지
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• 제22권1호
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• pp.30-36
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• 2008

Underwater ambient noise originating from geophysical, biological, and man-made acoustic sources contains information on the source and the ocean environment. Such noise affectsthe performance of sonar equipment. In this paper, three steps are used to identify the ambient noise source, detection, feature extraction, and similarity measurement. First, we use the zero-crossing rate to detect the ambient noisesource from background noise. Then, a set of feature vectors is proposed forthe ambient noise source using the Hilbert-Huang transform and the Karhunen-Loeve transform. Finally, the Euclidean distance is used to measure the similarity between the standard feature vector and the feature vector of the unknown ambient noise source. The developed algorithm is applied to the observed ocean data, and the results are presented and discussed.