• Title/Summary/Keyword: 기준 성장 곡선

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Population Forecasting System Based on Growth Curve Models (성장곡선모형에 의한 인구예측 시스템)

  • 최종후;최봉호;양우성;김유진
    • Korea journal of population studies
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    • v.23 no.1
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    • pp.197-215
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    • 2000
  • 이 논문에서는 선형·비선형 성장곡선모형의 종류와 특성을 살펴보고, 이들을 비교·검토하고, 모형선호기준 통계량에 입각하여 추정결과를 비교한다. 또한 최종사용자 환경을 위한 SAS/AF로 구현한 성장곡선모형에 의한 인구예측시스템을 소개한다.

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Construction of a reference stature growth curve using spline function and prediction of final stature in Korean (스플라인 함수를 이용한 한국인 키 기준 성장 곡선 구성과 최종 키 예측 연구)

  • An, Hong-Sug;Lee, Shin-Jae
    • The korean journal of orthodontics
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    • v.37 no.1 s.120
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    • pp.16-28
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    • 2007
  • Objective: Evaluation of individual growth is important in orthodontics. The aim of this study was to develop a convenient software that can evaluate current growth status and predict further growth. Methods: Stature data of 2 to 20 year-old Koreans (4893 boys and 4987 girls) were extracted from a nationwide data. Age-sex-specific continuous functions describing percentile growth curves were constructed using natural cubic spline function (NCSF). Then, final stature prediction algorithm was developed and its validity was tested using longitudinal series of stature measurements on randomly selected 200 samples. Various accuracy measurements and analyses of errors between observed and predicted stature using NCSF growth curves were performed. Results: NCSF growth curves were shown to be excellent models in describing reference percentile stature growth curie over age. The prediction accuracy compared favorably with previous prediction models, even more accurate. The current prediction models gave more accurate results in girls than boys. Although the prediction accuracy was high, the error pattern of the validation data showed that in most cases, there were a lot of residuals with the same sign, suggestive of autocorrelation among them. Conclusion: More sophisticated growth prediction algorithm is warranted to enhance a more appropriate goodness of model fit for individual growth.

Outlier Detection in Growth Curve Model Using Mean-Shift Model (평균이동모형을 이용한 성장곡선모형의 이상점 진단에 관한 연구)

  • Shim, Kyu-Bark
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.369-385
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    • 1999
  • For the growth curve model with arbitrary covariance structure, known as unstructured covariance matrix, the problems of detecting outliers are discussed in this paper. In order to detect outliers in the growth curve model, the likelihood ratio testing statistics in mean shift model is established and its distribution is derived. After we detected outliers in growth curve model, we test homo and/or hetero-geneous covariance matrices using PSR Quasi-Bayes Criterion. For illustration, one numerical example is discussed, which compares between before and after outlier deleting.

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Optical Properties of InAs Quantum Dots Grown by Using Arsenic Interruption Technique

  • Choe, Yun-Ho;Kim, Hui-Yeon;Ryu, Mi-Lee;Jo, Byeong-Gu;Kim, Jin-Su
    • Proceedings of the Korean Vacuum Society Conference
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    • 2011.08a
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    • pp.268-268
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    • 2011
  • GaAs (001) 기판에 MBE를 이용하여 자발형성법으로 성장한 InAs 양자점(QDs: quantum dots)의 광학적 특성을 PL (photoluminescence)과 TRPL (time-resolved PL)을 이용하여 분석하였다. InAs 양자점 성장 동안 In 공급은 계속하면서 As 공급을 주기적으로 차단과 공급을 반복하면서 성장하였다. As 차단과 공급을 1초, 2초, 그리고 3초씩 하면서 InAs 양자점을 성장하였다. 기준시료는 In과 As 공급을 중단하지 않고 20초 동안 성장하였다. As interruption mode로 성장한 시료들의 QD density는 기준시료에 비해 증가하였으며, size distribution도 기준시료에 비해 향상되었다. 기준시료와 비교하였을 때, As interruption mode로 성장한 시료들의 PL 피크는 적색이동 (red-shift)를 보였으며, PL 세기는 2배 이상 증가하였다. PL 소멸곡선은 파장이 증가함에 따라 점차 느려지다가 PL 피크에서 가장 느린 소멸을 보인 후 다시 점차 빠르게 소멸하였다. 시료의 온도를 10 K에서 60 K까지 증가하였을 때 PL 피크 에너지는 변하지 않았으며, PL 소멸시간은 서서히 증가함을 보였다. 온도를 더 증가하였을 때 PL 피크 에너지는 적색이동 하였으며 PL 소멸시간도 빠르게 감소함을 보였다. As interruption mode로 성장한 양자점 시료의 구조적 특성 변화에 의한 광학적 특성 변화를 확인하였다.

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Prediction of Fire Curves Considering the Relationship between Mass Increase and Combustion Time of Combustibles (연소물의 질량증가와 연소시간의 상관관계를 고려한 화재곡선 예측)

  • Eun-Joon Nam;Tae-Il Lee;Goang-Seup Zi
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.28 no.2
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    • pp.9-16
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    • 2024
  • In this paper, we aimed to convert the fire curve in volume units to a fire curve per unit area for application in the Fire Dynamic Simulator (FDS) surface heat release rate method. The fire curve was expressed dimensionlessly considering the total combustion characteristic time, and improvements were made to represent the appropriate ratios for the growth , steady, and decay phases concerning the fire intensity. Additionally, a correction function for combustion characteristic time varying with mass increase was derived. Also to control the growth time values according to the increase in mass, a function to correct the growth phase ratio was derived. Consequently, utilizing existing data, a formula was established to determine the reference mass for combustion materials and predict the fire curve based on mass increase.

Genetic Aspects of the Growth Curve Parameters in Hanwoo Cows (한우 암소의 성장곡선 모수에 대한 유전적 경향)

  • Lee, Chang-U;Choe, Jae-Gwan;Jeon, Gi-Jun;Kim, Hyeong-Cheol
    • Journal of Animal Science and Technology
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    • v.48 no.1
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    • pp.29-38
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    • 2006
  • The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were -0.47 and -0.67 using modelⅠand -0.56 and -0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were -0.26 and 0.01 using modelⅠand -0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were -0.49 and -0.67 suing model Ⅰ and -0.57 and -0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were -0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were -0.43 and -0.67 using model Ⅰ and -0.50 and -0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were -0.09 and 0.02 using model Ⅰ and -0.02 and 0.13 using model Ⅱ.

Optimum Designs of Fatigue Life Tests for Inverse Gaussian Distribution (역정규분포에 대한 피로수명시험의 최적설계)

  • 최규명;이낙영
    • The Korean Journal of Applied Statistics
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    • v.12 no.2
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    • pp.621-631
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    • 1999
  • 재료의 피로 파괴과정은 균열의 발생과 전파 및 성장의 과정을 거쳐 마침내 결정적 균열의 크기가 일정한도를 넘어서면 재료의 파괴가 일어난다. 이 때까지의 시간, 즉 피로 수명이 역정규분포를 따를 때 재료의 수명과 스트레스 수준과 관계를 나타 내는 S-N곡선에 대한 대수선형모형(log-linear model)을 제시하고, 이 모형하에서 피로수명시험에 대한 통계적 최적시험설계방법을 찾는다. 통계적 최적여부에 대한 판단기준으로 설계 스트레스 수준하의 특정 시점에서의 신뢰도에 대한 최우추정량의 점근분산을 최소화하는 방법을 사용하였다.

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Type 347 stainless steel 피로시험 데이터의 통계처리

  • Min, Gi-Deuk;Kim, Seon-Jin
    • Proceedings of the Materials Research Society of Korea Conference
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    • 2009.11a
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    • pp.35.2-35.2
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    • 2009
  • 최근 전세계적으로 저탄소, 녹색성장으로 인하여 원자력발전이 주목받고 있다. 또한 에너지의 고효율로 인한 발전소의 설비가 대형화가 됨에 따라 발전소의 수명평가와 건전성평가가 중요해지고 있다. 일반적으로 구조물 내에 존재하는 균열의 크기와 형상을 파악하여 피로균열전파속도를 평가함으로써 건전성평가를 확인하고 있다. 그리고 고온, 고압에서의 피로균열전파속도는직류전위차 (Direct Current Potential Drop : DCPD)법을 사용하고 있다. DCPD법은 균열의 정밀한 측정방법으로써 측정시 오차가 발생하기 때문에 ASTM에서 제시된 incremental polynomial 법을 권고하고 있다. 따라서 본 연구에서는 피로균열전파전파속도의통계적처리를 통해서 합리적인 곡선을 구하여 건전성평가에 활용하고자 한다. 실험에 사용된 시편은 두께 5mm, 폭 25.4mm CT시편을 사용하였으며, 1mm의 예비균열을 주었다. 그리고 실험온도는 상온에서 실시 하였으며, 주파수는 10Hz를 주었다. 그리고 DCPD 측정을 위해 5A의 전류를 주었으며, 이때 측정된 전압값을 ASTM에 제시된 관계식에넣어 균열길이로 환산하였으며, 데이터처리는 ASTM에 제시된 incremental polynomial법을 기본적으로 사용하였다. 또한 ASTM에 제시된 2n+1을 이용하여 데이터의 수 n을 1~7 까지 변화를 주어 3~15 point 까지 데이터를 처리하여곡선을 제시하였다. 분석결과 $R^2$값이 1을 기준으로 했을 때 3~7 point 까지는큰 차이를 보이지 않았지만 9-point 이후부터는 $R^2$ 감소함을 알 수 있었다. 또한 적용된 데이터의수에 따라 피로군열전파속도 곡선에서 측정된 Paris law의 n값과 C 값은 큰차이를 보이지 않았다.

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A Study on the make Fire Scenario for Residential Facility Combustible Materials

  • Kim, Dong-Eun;Lee, Dong-Yeol
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.6
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    • pp.137-143
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    • 2021
  • In the case of residential facilities, general fire scenarios cannot be applied. Becauseit is difficult to quantify due to the types of combustibles and various fire loads. Existing research conducting surveys of combustibles, but research on fire characteristics is insufficient. Therefore, in this study, an Excel macro that can be quantified by experimenting with the HRR experiments of sofa, drawer, mattress, chair, desk and TV, which are typical combustibles. As a result of experimenting 6 loading combustibles in domestic residential facilities by using a furniture calorimeter, values of 2,391.26kW appeared from the sofa, 1,891.80kW from the drawer, 1,778.95kW from the mattress, 1,104kW from the chair, 291kW from the desk, and 135.09kW from the TV. Also, by applying the α value of the fire growth rate by classifying fire-growing speeds at NFPA 72 (National Fire Alarm Code 2007, Annex B), the mattress can be defined as Very Fast, the sofa and drawer Fast, the TV Slow, the desk Slow, and the chair Medium.

Bivariate regional frequency analysis of extreme rainfalls in Korea (이변량 지역빈도해석을 이용한 우리나라 극한 강우 분석)

  • Shin, Ju-Young;Jeong, Changsam;Ahn, Hyunjun;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.51 no.9
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    • pp.747-759
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    • 2018
  • Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.