• Title/Summary/Keyword: 트리 회귀

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Segmental duration modelling for Korean text-to-speech synthesis (한국어 음성합성에서 음운지속시간 모델화)

  • Lee YangHee
    • Proceedings of the KSPS conference
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    • 1996.02a
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    • pp.125-135
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    • 1996
  • 본 논문에서는 자연스러운 음성을 합성하기 위하여, 한국어 음운지속시간의 변화에 있어서 문절과 구내의 음절수와 음절의 위치에 의한 영향과 인접하는 음운의 영향에 대하여 통계적으로 분석하였고, 분석된 시간 특징을 제어 요소로 하는 회귀트리를 생성하여 음운 지속시간을 모델 화하였다. 또한, 제안된 음운 지속시간 모델에 의해 예측실험을 행하여, 측정치와 예측치간의 다중 상관계수가 0.74정도이고, 각 음운의 예측오차의 75%이상이 25ms이내로 제안된 모델의 타당성이 입증되었다.

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Demographic Change and Easing Shrinkage in Urban Centers of Metropolises (대도시 도심부의 인구변동과 쇠퇴 양상의 변화 - 도심쇠퇴의 이완과 도심회귀 증후의 검토 -)

  • Yim, Seokhoi
    • Journal of the Korean association of regional geographers
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    • v.22 no.3
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    • pp.599-614
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    • 2016
  • Urban centers have been recognized as problem regions so far. However, urban centers of metropolises take a new aspect in recent years as much as the negative influence of gentrification becomes a social issue. This paper analyzes the declining trend of urban centers in six metropolises - Seoul, Busan, Daegu, Incheon, Gwangju and Daejun from 1995 to 2010. As results of analysis, it is identified that the urban centers' shrinkage got moderated recently in the metropolises, even though their resurgence is not evident. Especially it is difficult to say longer that Jongro-Gu and Jung-Gu of Seoul are declining urban centers. Easing shrinkage is most outstanding in Jung-Gu, Daegu among local metropolises. Nevertheless, a serious obstacle such as high price of housing is in the process of obvious resurgence of urban center differently from the United States, Europe and Japan.

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A Multivariate Analysis of Korean Professional Players Salary (한국 프로스포츠 선수들의 연봉에 대한 다변량적 분석)

  • Song, Jong-Woo
    • The Korean Journal of Applied Statistics
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    • v.21 no.3
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    • pp.441-453
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    • 2008
  • We analyzed Korean professional basketball and baseball players salary under the assumption that it depends on the personal records and contribution to the team in the previous year. We extensively used data visualization tools to check the relationship among the variables, to find outliers and to do model diagnostics. We used multiple linear regression and regression tree to fit the model and used cross-validation to find an optimal model. We check the relationship between variables carefully and chose a set of variables for the stepwise regression instead of using all variables. We found that points per game, number of assists, number of free throw successes, career are important variables for the basketball players. For the baseball pitchers, career, number of strike-outs per 9 innings, ERA, number of homeruns are important variables. For the baseball hitters, career, number of hits, FA are important variables.

Pattern Analysis of Traffic Accident data and Prediction of Victim Injury Severity Using Hybrid Model (교통사고 데이터의 패턴 분석과 Hybrid Model을 이용한 피해자 상해 심각도 예측)

  • Ju, Yeong Ji;Hong, Taek Eun;Shin, Ju Hyun
    • Smart Media Journal
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    • v.5 no.4
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    • pp.75-82
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    • 2016
  • Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

Head Pose Estimation Based on Perspective Projection Using PTZ Camera (원근투영법 기반의 PTZ 카메라를 이용한 머리자세 추정)

  • Kim, Jin Suh;Lee, Gyung Ju;Kim, Gye Young
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.7
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    • pp.267-274
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    • 2018
  • This paper describes a head pose estimation method using PTZ(Pan-Tilt-Zoom) camera. When the external parameters of a camera is changed by rotation and translation, the estimated face pose for the same head also varies. In this paper, we propose a new method to estimate the head pose independently on varying the parameters of PTZ camera. The proposed method consists of 3 steps: face detection, feature extraction, and pose estimation. For each step, we respectively use MCT(Modified Census Transform) feature, the facial regression tree method, and the POSIT(Pose from Orthography and Scaling with ITeration) algorithm. The existing POSIT algorithm does not consider the rotation of a camera, but this paper improves the POSIT based on perspective projection in order to estimate the head pose robustly even when the external parameters of a camera are changed. Through experiments, we confirmed that RMSE(Root Mean Square Error) of the proposed method improve $0.6^{\circ}$ less then the conventional method.

Degradation Diagnosis of Complex System Using Regression Analysis (회귀분석을 이용한 복합 시스템의 열화진단)

  • 김성홍;박재준;김재환
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.13 no.1
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    • pp.39-45
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    • 1999
  • Because of internal voids in insulators give rise to partial discharge(PD), which cause local breakdown and even entire insulation breakdown. Treeing due to PD is one of the main causes of breakdown of the insulating materials and nrluction of the insulation life. 1berefore the necessity for establishing a rrethod to diagnose the aging of insulation materials and to predict the breakdown of insulation has becorne irrportant. From this viewpoint, our studies diagnose insulation degradation using the rrethod of computer sensing system, which has PD and acoustic emission(AE) sensing system. To use advantages of these two methods can be used effectiveiy to search for treeing location and PD in sorre materials. In analysis rrethod of degradation, we analyzed the PD and AE pulses by regression analysis, corrpared to these obtained the correlation coefficient and retermination coefficient by T-distribution and saw that PD and AE pulses show a similar pattern on the whole. This has a similar teIlrency to the results of the research by Yoshimura and Fujita.Fujita.

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Analyzing the Factors of Gentrification After Gradual Everyday Recovery

  • Yoon-Ah Song;Jeongeun Song;ZoonKy Lee
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.8
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    • pp.175-186
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    • 2023
  • In this paper, we aim to build a gentrification analysis model and examine its characteristics, focusing on the point at which rents rose sharply alongside the recovery of commercial districts after the gradual resumption of daily life. Recently, in Korea, the influence of social distancing measures after the pandemic has led to the formation of small-scale commercial districts, known as 'hot places', rather than large-scale ones. These hot places have gained popularity by leveraging various media and social networking services to attract customers effectively. As a result, with an increase in the floating population, commercial districts have become active, leading to a rapid surge in rents. However, for small business owners, coping with the sudden rise in rent even with increased sales can lead to gentrification, where they might be forced to leave the area. Therefore, in this study, we seek to analyze the periods before and after by identifying points where rents rise sharply as commercial districts experience revitalization. Firstly, we collect text data to explore topics related to gentrification, utilizing LDA topic modeling. Based on this, we gather data at the commercial district level and build a gentrification analysis model to examine its characteristics. We hope that the analysis of gentrification through this model during a time when commercial districts are being revitalized after facing challenges due to the pandemic can contribute to policies supporting small businesses.

Robust Backward Adaptive Pitch Prediction for Tree Coding (트리 코팅에서 전송에러에 강한 역방향 적응 피치 예측)

  • 이인성
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.8
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    • pp.1587-1594
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    • 1994
  • The pitch predictor is one of the most important part for the robust tree coder. The hybrid backward pitch adapation which is a combination of a block adaptation and a recursive adaptation is used for the pitch predictor. In order to improve the error performance and track the pitch period change of the input speech, it is proposed to smooth the input of the pitch predictor. The smoother with three taps can have fixed coefficients or variable coefficients depending on the estimated autocorrelation function of the output of the pitch synthesizer. The inclusion of a variable smoother can track the pitch period change within a block and reduce the effect of channel errors.

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A Comparative Study on Game-Score Prediction Models Using Compuational Thinking Education Game Data (컴퓨팅 사고 교육 게임 데이터를 사용한 게임 점수 예측 모델 성능 비교 연구)

  • Yang, Yeongwook
    • KIPS Transactions on Software and Data Engineering
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    • v.10 no.11
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    • pp.529-534
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    • 2021
  • Computing thinking is regarded as one of the important skills required in the 21st century, and many countries have introduced and implemented computing thinking training courses. Among computational thinking education methods, educational game-based methods increase student participation and motivation, and increase access to computational thinking. Autothinking is an educational game developed for the purpose of providing computational thinking education to learners. It is an adaptive system that dynamically provides feedback to learners and automatically adjusts the difficulty according to the learner's computational thinking ability. However, because the game was designed based on rules, it cannot intelligently consider the computational thinking of learners or give feedback. In this study, game data collected through Autothikning is introduced, and game score prediction that reflects computational thinking is performed in order to increase the adaptability of the game by using it. To solve this problem, a comparative study was conducted on linear regression, decision tree, random forest, and support vector machine algorithms, which are most commonly used in regression problems. As a result of the study, the linear regression method showed the best performance in predicting game scores.

Unsupervised Word Grouping Algorithm for real-time implementation of Medium vocabulary recognition (중규모급 단어 인식기의 실시간 구현을 위한 무감독 단어집단화 알고리듬)

  • Lim Dong Sik;Kim Jin Young;Baek Seong Joon
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.81-84
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    • 1999
  • 본 논문에서는 중규모급 단어인식기의 실시간 구현을 위한 무감독 단어집단화 알고리듬을 제안한다. 무감독 단어집단화는 인식대상 어휘 수가 많은 대용량 음성인식 시스템에서 대상 어휘 수를 줄여주는 역할을 하는 전처리기의 성격을 갖는다. 무감독 집단화를 위해 각 단어의 유$\cdot$무성음 고유의 특성을 잘 반영할 수 있는 특징 파라미터 5개를 사용하여 패턴 인식과 회귀분석에서 널리 사용되고 있는 분류$\cdot$회귀트리(Classification And Regression Tree)에 적용시키는 방법으로 접근하였고, 각 단어의 frame 수를 일정하게 n개로 분할(segment)하여 1개의 tree를 생성시키는 방법과 각 segment에 해당하는 tree를 생성시켜 segment들 사이의 교집합 성분으로 단어들을 집단화 하였다 실험결과 탐색 대상단어 22개에서 평균2.21개로 줄어 전체 대상 단어의 $10\%$만을 탐색하여 인식할 수 있는 방법을 제시할 수 있었다.

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