• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.817-826
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• 2007

The existing a music genre classification research used signal feature of the part which gets 20 seconds interval of the random or the $40%{\sim}45%$ after in the music. This paper propose it to increase the accuracy of existing research to classify music genre using climax part in the music. Generally the music is divided to three parts; introduction, progress and climax. And the climax is the part which the music emphasizes and expresses the feature of the music best. So, we can get efficient result if the climax is used, when the music classify. We can get the climax in the music finding the tempo and node which uses FFT and the maximum waveform from each node. In this paper, we did a genre classification experiment which uses existing research method and proposing method. The existing method expressed 47% accuracy. And proposing method expressed 56% accuracy which is improved than existing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.1-11
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• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• Korean Journal of Weed Science
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• v.31 no.1
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• pp.49-70
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• 2011

This study was conducted to examine the change of flora and plant species diversity between 2005 and 2010 in Yangjaecheon (stream) which was divided among three different types of vegetation management method; ecological vegetation management (weeding vines and invasive plants; EVM), plant cultivation (PC) and uncared for vegetation (UC). There were total 478 taxa, composed by 429 spontaneous taxa and 49 cultivated taxa in 2005 and total 424 taxa composed by 318 spontaneous taxa and 106 cultivated taxa in 2010. In spontaneous plants, 201 taxa were distributed over total area, 197 taxa were distributed in only EVM area, 10 taxa in only PC area and 59 taxa in only UC area. Also, the most dominant family (Asteraceae${\rightarrow}$Poaceae) and number of rare taxa (reduced) and wide distributed taxa (increased) was changed from 2005 to 2010. The rate of perennial taxa was found to be increased in only EVM area. In conclusion, EVM is thought to be a more efficient method for plant species diversity of restored stream.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.2 s.48
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• pp.63-71
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• 2006

In the companion paper (II, Development of Site Classification System), new size classification system based on site periods $(T_G)$ was recommended for legions of shallow bedrock depth in Korea. Despite the site classification method was improved, the response spectrum would be required to be modified by adjusting the integration interval to calculate the site coefficients because the response spectra did not match well the average spectral accelerations obtained by site response analyses in the range of long periods. In this paper, new response spectra for each site categories were determined by adjusting the integration interval of long period site coefficient $F_v\;from\;0.4{\sim}2.0\;to\;0.4{\sim}1.5$ second. It matched well the average spectral accelerations and new response spectrum, and it was also improved compared to the current she classification system.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.43-51
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• 2023

In this paper, we propose an approach for dialect classification based on the speed and pause of speech utterances as well as the age and gender of the speakers. Dialect classification is one of the important techniques for speech analysis. For example, an accurate dialect classification model can potentially improve the performance of speaker or speech recognition. According to previous studies, research based on deep learning using Mel-Frequency Cepstral Coefficients (MFCC) features has been the dominant approach. We focus on the acoustic differences between regions and conduct dialect classification based on the extracted features derived from the differences. In this paper, we propose an approach of extracting underexplored additional features, namely the speed and the pauses of speech utterances along with the metadata including the age and the gender of the speakers. Experimental results show that our proposed approach results in higher accuracy, especially with the speech rate feature, compared to the method only using the MFCC features. The accuracy improved from 91.02% to 97.02% compared to the previous method that only used MFCC features, by incorporating all the proposed features in this paper.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.225-242
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• 2019

Rockfall failure at the access road to Seokguram were occurred due to the earthquake on September 12, 2016. A detailed investigation was carried out in order to find out the cause of the rockfall, to identify the risk of the entire sites, and to prepare proper countermeasure methods and mitigation. We checked for geological and topographical characteristics of overall slopes alongside the access road to Seokguram and made a face map. In addition, we analyzed topographical factors caused by the earthquake through calculating a degree of slope, degree of bearing, upslope contributing area, and wetness index with the use of shading relief map. As a result, we confirmed that the large rockfall occurred with a weak section. In this study, we also evaluated the overall slope stability of the entire access road to Seokguram in order to classify it into danger and caution zones depending on the risk of collapse.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.09a
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• pp.37-42
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• 2005

Remote seismic tomography is regarded as one of the most valuable geophysical technique for the estimation of the rock mass classification in the tunnel area where hard data information such as drill logs are absent. But the results of rock mass classification based on the remote seismic tomography tend to be overestimated in practice. In this study, we propose the effective method to implement the seismic reference velocity ratio based on semblance for the improvement of rock mass classification. Also, to verify its feasibility, proposed technique was tested by using the real field data.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.238-245
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• 2013

Gesture recognition has been widely one of the research areas for natural user interface. This paper presents a novel gesture recognition method using tree classification and multiclass SVM(Support Vector Machine). In the learning step, 3D trajectory of human gesture obtained by a Kinect sensor is classified into the tree nodes according to their distributions. The gestures are resampled and we obtain the histogram of the chain code from the normalized data. Then multiclass SVM is applied to the classified gestures in the node. The input gesture classified using the constructed tree is recognized with multiclass SVM.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1615-1618
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• 1987

This paper proposes new algorithm for classifying speech signal frame into voiced, unvoiced, silence frame, using the parameters extracted from time domain behavior of speech signal The prameters used in this paper are absolute magnitude, the sum of peaks lager than reference level (T-peak), the ratio of T-peak to absolute magnitude and the magnitude of signal outputs of DPCM. Using this parameters, speech signal is more easily classified into voiced/ unvoiced/silence frame.

• Journal of KIISE:Software and Applications
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• v.28 no.1
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• pp.64-72
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• 2001

결정트리 생성은 일련의 특징값으로 기술된 사례들로부터 분류 지식을 추출하는 학습 방법중의 하나이다. 현장에서 수집되는 사례들은 관측 오류, 주관적인 판단, 불확실성 등으로 인해서 애매하게 주어지는 경우가 많다. 퍼지숫자나 구간값을 사용함으로써 이러한 애매한 데이타의 수치 속성은 쉽게 표현될 수 있다. 이 논문에서는 수치 속성은 보통값 뿐마아니라 퍼지숫자나 구간값을 갖을 수 있고, 비수치 속서은 보통값을 가지며, 데이터의 클래스는 확신도를 기자는 학습 데이터들로 부터, 분류 규칙을 마이닝하기 위한 퍼지 결정트리 생성 방법을 제안한다. 또한 제안한 방법에 의해 생성된 퍼지 결정트리를 사용하여, 새로운 데이터에 대한 클래스를 결정하는 추론 방법을 소개한다. 한편, 제안된 방법의 유용성을 보이기 위해 수행한 실험의 결과를 보인다.