• Title/Summary/Keyword: 리듬 분류

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Comparison of Red Tide Algorithm for Coastal Red Tide Detection (연안적조관측을 위한 적조 알고리듬 비교)

  • 정종철
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.280-284
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    • 2003
  • 국내에서는 매년 연안에서 발생하는 적조에 의해 많은 수산자원의 피해를 입고 있다. 이를 방재하기 위해 다양한 기술이 연구 개발되고 있으며, 원격탐사기법의 활용이 연구되어 왔다. 그러나 위성자료에 의한 연안해역에서의 적조관측은 시-공간적인 범위에서 많은 제약을 받고 있으며, 이로 인해 위성자료의 분석을 위한 적조 알고리듬은 국내외적으로 제시된 바가 매우 미약하다. 본 연구에서는 다양한 위성자료에 의해 관측된 적조의 패취를 구분하고 이를 정성적으로 분류해내기 위한 적조 알고리듬을 비교하였다. 특히 시-공간해상력에서 많은 차이를 가지고 있는 Landsat TM, AVHRR, SeaWiFS의 위성자료를 비교하여 관측주기가 다르고 분광해상력에서 차이를 나타내는 이들 위성자료를 이용한 적조 관측 알고리듬의 활용 가능성을 비교하였다. 분석된 결과를 바탕으로 국내연안에서 발생한 적조의 공간적 분포를 구분화하고 이를 현장관측 자료와 비교하여 분석결과의 정확도를 평가하였다.

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Vehicle Detection and Classification Using Textural Similarity in Wavelet Domain (웨이브렛 영역에서의 질감 유사성을 이용한 차량검지 및 차종분류)

  • 임채환;박종선;이창섭;김남철
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.6B
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    • pp.1191-1202
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    • 1999
  • We propose an efficient vehicle detection and classification algorithm for an electronic toll collection using the feature which is robust to abrupt intensity change between consecutive frames. The local correlation coefficient between wavelet transformed input and reference images is used as such a feature, which takes advantage of textural similarity. The usefulness of the proposed feature is analyzed qualitatively by comparing the feature with the local variance of a difference image, and is verified by measuring the improvements in the separability of vehicle from shadowy or shadowless road for a real test image. Experimental results from field tests show that the proposed vehicle detection and classification algorithm performs well even under abrupt intensity change due to the characteristics of sensor and occurrence of shadow.

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A EMG Signal Processing Algorithm for SMUAP Pattern Classification (SMUAP의 패턴분류를 위한 근 신호처리 알고리듬)

  • Lee, Jin;Jo, Il-Jun;Byun, Youn-Shik;Hong, Woan-Hue;Kim, Sung-Hwan
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.7
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    • pp.106-111
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    • 1989
  • A new EMG signal processing algorithm for SMUAP pattern classification is proposed. It checks the combination and regularity of ISI using a spike counter as a decision making routine, and performs SMUAP waveform alignment in frequency domain and selects spikes through FIR filtering. As a result, with the EMG signals recorded during 5 seconds at 10-50% MVC force level, the SMUAP ranged from five to nine units were classified and identification rate is greater than 55 percent using a concentric needle electrode. In the IBM PC/AT the processing time typically required 2 minutes.

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Music Transcription Using Non-Negative Matrix Factorization (비음수 행렬 분해 (NMF)를 이용한 악보 전사)

  • Park, Sang-Ha;Lee, Seok-Jin;Sung, Koeng-Mo
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.2
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    • pp.102-110
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    • 2010
  • Music transcription is extracting pitch (the height of a musical note) and rhythm (the length of a musical note) information from audio file and making a music score. In this paper, we decomposed a waveform into frequency and rhythm components using Non-Negative Matrix Factorization (NMF) and Non-Negative Sparse coding (NNSC) which are often used for source separation and data clustering. And using the subharmonic summation method, fundamental frequency is calculated from the decomposed frequency components. Therefore, the accurate pitch of each score can be estimated. The proposed method successfully performed music transcription with its results superior to those of the conventional methods which used either NMF or NNSC.

Research on Types of Visual Rhythmic Sense in Typography (타이포그래피의 시각적 리듬감 유형 연구)

  • Jung, Yu-Kyung
    • Archives of design research
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    • v.18 no.2 s.60
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    • pp.143-154
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    • 2005
  • Typography in visual communication design is 'potential form' hidden within a space. Showing rhythm in typography is making 'aesthetic sense' in a graphic which has formative characteristics, the way of expression is very important. When the rhythm is recognized through visual stream, Rhythmic Sense is formed. The research will present a new form of the Visual Rhythmic Sense by analyzing typography works out positively. First of all, I researched works done by Fillippo Marinetti, Robert Massin, Wolfgang Weingart, and David Carson for their vigorous experimentalism in typography in forming visual rhythm. I used S.D. Scale method to analyze characteristics of visual image and VARIMAX for factor analysis reaching types of visual rhythm, which could be classified as following. (1) Synesthesia Rhythmic Sense (R-synesthesia) means that the senses are conveyed through 'visualization of auditory sense' and 'visualization of touch' (2) Simultaneous Rhythmic Sense (R-simultaneity) means that the time and space co-exist in one plane. (3) Connective Rhythmic Sense(R-connection) means that different factors (Within one plane) co-exist interacting with one another and creating a unified impression through such a process. (4) Artist Oriented Rhythmic Sense ($-artist) means that the artist interprets the content subjectively and expresses his/her impression, thereby, attracting a gaze of audience systematically and arbitrarily. (5) Reader Oriented Rhythmic Sense(R-reader) avoids the existing legibility formed through aggressive engagement of the reader.

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Aspects of Korean rhythm realization by second language learners: Focusing on Chinese learners of Korean (제 2언어 학습자의 한국어 리듬 실현양상 -중국인 한국어 학습자를 중심으로-)

  • Youngsook Yune
    • Phonetics and Speech Sciences
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    • v.15 no.3
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    • pp.27-35
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    • 2023
  • This study aimed to investigate the effect of Chinese on the production of Korean rhythm. Korean and Chinese are typologically classified into different rhythmic categories; because of this, the phonological properties of Korean and Chinese are similar and different at the same time. As a result, Chinese can exert both positive and negative influences on the realization of Korean rhythm. To investigate the influence of the rhythm of the native language of L2 learners on their target language, we conducted an acoustic analysis using acoustic metrics like of the speech of 5 Korean native speakers and 10 advanced Chinese Korean learners. The analyzed material is a short paragraph of five sentences containing a variety of syllable structures. The results showed that KS and CS rhythms are similar in %V, VarcoV, and nPVI_S. However, CS, unlike KS, showed characteristics closer to those of a stress-timed language in the values of %V and VarcoV. There was also a significant difference in nPVI_V values. These results demonstrate a negative influence of the native language in the realization of Korean rhythm. This can be attributed to the fact that all vowels in Chinese sentence are not pronounced with the same emphasis due to neutral tone. In this sense, this study allowed us to observe influences of L1 on L2 production of rhythm.

MRAL Post Processing based on LS for Performance Improvement of Active Sonar Localization (소나 위치 추정 성능 향상을 위한 LS기반 MRAL 후처리 기법)

  • Jang, Eun-Jeong;Han, Dong Seog
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.9
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    • pp.172-180
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    • 2012
  • In multi-static sonar for detecting an underwater target, received signals contain the target echo, reverberation and clutter. Clutter and reverberation are main causes of increasing the false alarm rate. MRAL classifies received signals according to the spatial similarity, and it regards classified signal as reflected signals from a reflector. MRAL reduces the false alarm rate this way. However, the results of MRAL can have localization errors. In this paper, an MRAL post processing algorithm is proposed to reduce the localization errors with the least square (LS) method.

Multi-Modal Scheme for Music Mood Classification (멀티 모달 음악 무드 분류 기법)

  • Choi, Hong-Gu;Jun, Sang-Hoon;Hwang, Een-Jun
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06a
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    • pp.259-262
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    • 2011
  • 최근 들어 소리의 세기나 하모니, 템포, 리듬 등의 다양한 음악 신호 특성을 기반으로 한 음악 무드 분류에 대한 연구가 활발하게 진행되고 있다. 본 논문에서는 음악 무드 분류의 정확도를 높이기 위하여 음악 신호 특성과 더불어 노래 가사와 소셜 네트워크 상에서의 사용자 평가 등을 함께 고려하는 멀티 모달 음악 무드 분류 기법을 제안한다. 이를 위해, 우선 음악 신호 특성에 대해 퍼지 추론 기반의 음악 무드 추출 기법을 적용하여 다수의 가능한 음악 무드를 추출한다. 다음으로 음악 가사에 대해 TF-IDF 기법을 적용하여 대표 감정 키워드를 추출하고 학습시킨 가사 무드 분류기를 사용하여 가사 음악 무드를 추출한다. 마지막으로 소셜 네트워크 상에서의 사용자 태그 등 사용자 피드백을 통한 음악 무드를 추출한다. 특정 음악에 대해 이러한 다양한 경로를 통한 음악 무드를 교차 분석하여 최종적으로 음악 무드를 결정한다. 음악 분류를 기반한 자동 음악 추천을 수행하는 사용자 만족도 평가 실험을 통해서 제안하는 기법의 효율성을 검증한다.

Heart Sound-Based Cardiac Disorder Classifiers Using an SVM to Combine HMM and Murmur Scores (SVM을 이용하여 HMM과 심잡음 점수를 결합한 심음 기반 심장질환 분류기)

  • Kwak, Chul;Kwon, Oh-Wook
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.3
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    • pp.149-157
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    • 2011
  • In this paper, we propose a new cardiac disorder classification method using an support vector machine (SVM) to combine hidden Markov model (HMM) and murmur existence information. Using cepstral features and the HMM Viterbi algorithm, we segment input heart sound signals into HMM states for each cardiac disorder model and compute log-likelihood (score) for every state in the model. To exploit the temporal position characteristics of murmur signals, we divide the input signals into two subbands and compute murmur probability of every subband of each frame, and obtain the murmur score for each state by using the state segmentation information obtained from the Viterbi algorithm. With an input vector containing the HMM state scores and the murmur scores for all cardiac disorder models, SVM finally decides the cardiac disorder category. In cardiac disorder classification experimental results, the proposed method shows the relatively improvement rate of 20.4 % compared to the HMM-based classifier with the conventional cepstral features.

Input Pattern Vector Extraction and Pattern Recognition of EEG (뇌파의 입력패턴벡터 추출 및 패턴인식)

  • Lee, Yong-Gu;Lee, Sun-Yeob;Choi, Woo-Seung
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.95-103
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    • 2006
  • In this paper, the input pattern vectors are extracted and the learning algorithms is designed to recognize EEG pattern vectors. The frequency and amplitude of alpha rhythms and beta rhythms are used to compose the input pattern vectors. And the algorithm for EEG pattern recognition is used SOM to learn initial reference vectors and out-star learning algorithm to determine the class of the output neurons of the subclass layer. The weights of the proposed algorithm which is between the input layer and the subclass layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm, and pattern vectors is classified into subclasses by neurons which is being in the subclass layer, and the weights between subclass layer and output layer is learned to classify the classified subclass, which is enclosed a class. To classify the pattern vectors of EEG, the proposed algorithm is simulated with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional LVQ.

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