• Title/Summary/Keyword: DTW(Dynamic Time Warping)

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Development of melody similarity based on chroma representation, dynamic time warping, and hinge distance (크로마 레벨 표현, 동적 시간 왜곡, 꺾인 거리함수에 기반한 멜로디 사이의 유사도 개발)

  • Jang, Dalwon;Park, Sung-Ju;Jang, Sei-Jin;Lee, Seok-Pil
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.07a
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    • pp.258-260
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    • 2011
  • 이 논문에서는 쿼리-바이-싱잉/허밍 (Query-by-singing/humming, QbSH) 시스템 또는 커버 노래 인식 (cover song identification) 시스템에서 사용 가능한 멜로디 유사도를 제안한다. QbSH 또는 커버 노래 인식은 디지털 음악의 사용이 보편화되면서 음악 검색의 방법으로 많은 연구가 진행되어 오고 있다. 멜로디 유사도는 이런 시스템을 구현하는데 필수적인 요소이며, 두 개의 음악에서 멜로디가 추출되었다고 가정하고, 추출된 멜로디 사이의 유사한 정도를 수치로 표현한다. QbSh 시스템이나 커버 노래 인식 시스템은 멜로디 유사도에 기반하여 입력 노래와 유사한 노래를 데이터베이스에서 검색하는 작업을 수행한다. 이 논문에서 제안하는 멜로디 유사도 방식은 기존의 많이 연구되던 동적 시간 왜곡 (dynamic time warping, DTW) 방법과 크로마 표현 방법 (chroma representation)을 사용하였다. DTW방법은 비대칭적으로 사용하고 미디 노트 영역에서 표현된 멜로디 특징은 0이상 12 미만의 크로마 레벨로 표현하였다. 기존의 방법에서는 정수값을 많이 사용하였으나 이 논문에서는 실수값을 사용한다. DTW 에 사용하는 거리 함수를 기존에 사용하던 차이의 절대값 대신 꺾인 함수 형태를 사용함으로써 성능을 높였다. QbSH 시스템에서의 실험을 통해서 성능을 검증하였다. 본 논문에서는 10-12초 길이의 1000번의 쿼리(Query)에 대해서 28시간 정도의 데이터베이스에서 실험한 결과, 순위 역의 평균 (Mean reciprocal rank, MRR) 값이 0.713을 보였다.

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Similarity Measurement Method of Trajectory using Indexing Information of Moving Object in Video (비디오 내 이동 객체의 색인 정보를 이용한 궤적 유사도 측정 기법)

  • Kim, Jeong In;Choi, Chang;Kim, Pan Koo
    • Smart Media Journal
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    • v.1 no.3
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    • pp.43-47
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    • 2012
  • The recent proliferation of multimedia data necessitates the effectively and efficiently retrieving of multimedia data. These research not only focus on the retrieving methods of text matching but also on using the multimedia data features. Therefore, this paper is a similarity measurement method of trajectory using indexing information of moving object in video, for similarity measurement. This method consists of 2 steps. Firstly, Video data is processed indexing for trajectory extraction of moving objects using CCTV. Finally, we describe to compare DTW(Dynamic Time Warping) to TSR(Tansent Space Representation) algorithm.

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Relationship between Aiming Patterns and Scores in Archery Shooting

  • Quan, ChengHao;Lee, Sangmin
    • Korean Journal of Applied Biomechanics
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    • v.26 no.4
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    • pp.353-360
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    • 2016
  • Objective: The aim of this study was to investigate the relationship between aiming patterns and scores in archery shooting. Method: Four (N = 4) elementary-level archers from middle school participated in this study. Aiming pattern was defined by averaged acceleration data measured from accelerometers attached on the body during the aiming phase in archery shooting. Stepwise multiple regression analysis was used to test whether a model incorporating aiming patterns from all nine accelerometers could predict the scores. In order to extract period of interest (POI) data from raw data, a Dynamic Time Warping (DTW)-based extraction method was presented. Results: Regression models for all four subjects are conducted with different significance levels and variables. The significance levels of the regression models are 0.12%, 1.61%, 0.55%, and 0.4% respectively; the $R^2$ of the regression models is 64.04%, 27.93%, 72.02%, and 45.62% respectively; and the maximum significance levels of parameters in the regression models are 1.26%, 4.58%, 5.1%, and 4.98% respectively. Conclusion: Our results indicated that the relationship between aiming patterns and scores was described by a regression model. Analysis of the significance levels, variables, and parameters of the regression model showed that our approach - regression analysis with DTW - is an effective way to raise scores in archery shooting.

FAULT DIAGNOSIS OF ROLLING BEARINGS USING UNSUPERVISED DYNAMIC TIME WARPING-AIDED ARTIFICIAL IMMUNE SYSTEM

  • LUCAS VERONEZ GOULART FERREIRA;LAXMI RATHOUR;DEVIKA DABKE;FABIO ROBERTO CHAVARETTE;VISHNU NARAYAN MISHRA
    • Journal of applied mathematics & informatics
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    • v.41 no.6
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    • pp.1257-1274
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    • 2023
  • Rotating machines heavily rely on an intricate network of interconnected sub-components, with bearing failures accounting for a substantial proportion (40% to 90%) of all such failures. To address this issue, intelligent algorithms have been developed to evaluate vibrational signals and accurately detect faults, thereby reducing the reliance on expert knowledge and lowering maintenance costs. Within the field of machine learning, Artificial Immune Systems (AIS) have exhibited notable potential, with applications ranging from malware detection in computer systems to fault detection in bearings, which is the primary focus of this study. In pursuit of this objective, we propose a novel procedure for detecting novel instances of anomalies in varying operating conditions, utilizing only the signals derived from the healthy state of the analyzed machine. Our approach incorporates AIS augmented by Dynamic Time Warping (DTW). The experimental outcomes demonstrate that the AIS-DTW method yields a considerable improvement in anomaly detection rates (up to 53.83%) compared to the conventional AIS. In summary, our findings indicate that our method represents a significant advancement in enhancing the resilience of AIS-based novelty detection, thereby bolstering the reliability of rotating machines and reducing the need for expertise in bearing fault detection.

A Performance Enhancement of Container ISO-code Recognition using Dynamic Time Warping (Dynamic Time Warping을 이용한 컨테이너 식별자 인식 성능 향상)

  • Lee, Sang-Lyn;Koo, Kyung-Mo;Cha, Eui-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.977-980
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    • 2007
  • 본 논문은 인식된 컨테이너 식별자 문자열과 컨테이너 작업리스트를 비교하여 작업리스트와 인식된 컨테이너 식별자 문자열을 매칭하는 효율적인 방법을 소개하고자 한다. Dynamic Time Warping 기법을 이용하여 오인식되거나 인식이 되지 않은 문자에 대하여 오독률을 최소화할 수 있는 효율적인 방법을 제안한다. 기존의 문자열 비교방식에 비하여 제안하는 방법을 사용하였을 경우 더 나은 성능을 보였다.

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Image Information Retrieval Using DTW(Dynamic Time Warping) (DTW(Dynamic Time Warping)를 이용한 영상 정보 검색)

  • Ha, Jeong-Yo;Lee, Na-Young;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of Digital Contents Society
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    • v.10 no.3
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    • pp.423-431
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    • 2009
  • There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

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Same music file recognition method by using similarity measurement among music feature data (음악 특징점간의 유사도 측정을 이용한 동일음원 인식 방법)

  • Sung, Bo-Kyung;Chung, Myoung-Beom;Ko, Il-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.3
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    • pp.99-106
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    • 2008
  • Recently, digital music retrieval is using in many fields (Web portal. audio service site etc). In existing fields, Meta data of music are used for digital music retrieval. If Meta data are not right or do not exist, it is hard to get high accurate retrieval result. Contents based information retrieval that use music itself are researched for solving upper problem. In this paper, we propose Same music recognition method using similarity measurement. Feature data of digital music are extracted from waveform of music using Simplified MFCC (Mel Frequency Cepstral Coefficient). Similarity between digital music files are measured using DTW (Dynamic time Warping) that are used in Vision and Speech recognition fields. We success all of 500 times experiment in randomly collected 1000 songs from same genre for preying of proposed same music recognition method. 500 digital music were made by mixing different compressing codec and bit-rate from 60 digital audios. We ploved that similarity measurement using DTW can recognize same music.

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Analysis of intraday price momentum effect based on patterns using dynamic time warping (DTW를 이용한 패턴 기반 일중 price momentum 효과 분석)

  • Lee, Chunju;Ahn, Wonbin;Oh, Kyong Joo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.4
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    • pp.819-829
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    • 2017
  • The aim of this study is to analyze intraday price momentum. When price trends are formed, price momentum is the phenomenon that future prices tend to follow the trend. When the market opened and closed, a U-shaped trading volume pattern in which the trading volume was concentrated was observed. In this paper, we defined price momentum as the 10 minute trend after market opening is maintained until the end of market. The strategy is to determine buying and selling in accordance with the price change in the initial 10 minutes and liquidating at closing price. In this study, the strategy was empirically analyzed by using minute data, and it showed effectiveness, indicating the presence of an intraday price momentum. A pattern in which returns are increasing at an early stage is called a J-shaped pattern. If the J-shaped pattern occurs, we have found that the price momentum phenomenon tends to be stronger than otherwise. The DTW algorithm, which is well known in the field of pattern recognition, was used for J-shaped pattern recognition and the algorithm was effective in predicting intraday price movements. This study showed that intraday price momentum exists in the KOSPI200 futures market.

A study on electricity demand forecasting based on time series clustering in smart grid (스마트 그리드에서의 시계열 군집분석을 통한 전력수요 예측 연구)

  • Sohn, Hueng-Goo;Jung, Sang-Wook;Kim, Sahm
    • The Korean Journal of Applied Statistics
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    • v.29 no.1
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    • pp.193-203
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    • 2016
  • This paper forecasts electricity demand as a critical element of a demand management system in Smart Grid environment. We present a prediction method of using a combination of predictive values by time series clustering. Periodogram-based normalized clustering, predictive analysis clustering and dynamic time warping (DTW) clustering are proposed for time series clustering methods. Double Seasonal Holt-Winters (DSHW), Trigonometric, Box-Cox transform, ARMA errors, Trend and Seasonal components (TBATS), Fractional ARIMA (FARIMA) are used for demand forecasting based on clustering. Results show that the time series clustering method provides a better performances than the method using total amount of electricity demand in terms of the Mean Absolute Percentage Error (MAPE).

The Optical Tracking Method of Flight Target using Kalman Filter with DTW (DTW와 Kalman Filter를 결합한 비행표적의 광학추적 방법)

  • Jang, Sukwon
    • Journal of Advanced Navigation Technology
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    • v.25 no.3
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    • pp.217-222
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    • 2021
  • EOTS(Electro-Optical Tracking System) is utilized in acquiring visual information to assess a guided missile's performance. As the missile travels so fast, it is almost impossible for operator to re-capture the lost target. The RADAR or telemetry data are used to re-capture the lost target however facilities to receive real time data is required, which constrains selection of tracking site. Unlike aforementioned data, pre-calculated nominal trajectory can be used without communication facility. This paper proposes a method to predict lost target's state by employing nominal trajectory. Firstly, observed trajectory and nominal trajectory are compared using DTW and current target's state is predicted. The predicted state is used as observation in Kalman filter's correction phase to predict target's next state. The plausibility of the proposed method is verified by applying on actual missile trajectory.