• 제목/요약/키워드: Mixed-Data

검색결과 3,000건 처리시간 0.038초

현열 플럭스 추정에 의한 대류 혼합층 고도의 산출 (Calculation of the Convective Mixed Layer by Estimation of Sensible Heat Flux)

  • 김용국
    • 한국환경과학회지
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    • 제7권5호
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    • pp.639-645
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    • 1998
  • A Jump model was evaluated for the calculation of hourly mixing height and mean potential temperature within the height. The Sump model was modified for estimation of downward heat fluxes by mechanical convections and surface heat fluxes. The surface heat fluxes were estimated from routine weather data such as solar radiation and air temperature. Total of 8 upper-air data observed at 0000UTC and 0600UTC in Osan station during April 23 to 26, 1996 were analyzed, and compared to the model results in detail. The calculated mixing heights and potential temperatures within the height were comparable to the observations, but some differences were showed. The calculated mixing heights were generally higher than observations. And, when variations of wind directions were large, the large difference of potential temperature was occurred. From the results, it was important to note that vortical motions and advections of air masses would affect to the growth of the mixing height.

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An Optimized Strategy for Genome Assembly of Sanger/pyrosequencing Hybrid Data using Available Software

  • Jeong, Hae-Young;Kim, Ji-Hyun F.
    • Genomics & Informatics
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    • 제6권2호
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    • pp.87-90
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    • 2008
  • During the last four years, the pyrosequencing-based 454 platform has rapidly displaced the traditional Sanger sequencing method due to its high throughput and cost effectiveness. Meanwhile, the Sanger sequencing methodology still provides the longest reads, and paired-end sequencing that is based on that chemistry offers an opportunity to ensure accurate assembly results. In this report, we describe an optimized approach for hybrid de novo genome assembly using pyrosequencing data and varying amounts of Sanger-type reads. 454 platform-derived contigs can be used as single non-breakable virtual reads or converted to simpler contigs that consist of editable, overlapping pseudoreads. These modified contigs maintain their integrity at the first jumpstarting assembly stage and are edited by fragmenting and rejoining. Pre-existing assembly software then can be applied for mixed assembly with 454-derived data and Sanger reads. An effective method for identifying genomic differences between reference and sample sequences in whole-genome resequencing procedures also is suggested.

Load Cell Noise 제거를 위한 Digital Load Cell 에 대한 연구 (A study on a digital load cell for the removal of load cell noise)

  • 이영진;이흥호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.562-564
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    • 2002
  • Noise reduction and a simplification of a precision measurement system has been performed by changing analog output mode of a load cell into digital output mode. Usually, analog output signal of a few $\mu V$ from a load cell are amplified by amp and acquired by A/D converter. If the distance from a load cell to a DAS(Data Acquisition System) increases, more noise signals are mixed. So, a microprocessor has been integrated into a load cell so that the amplification and A/D conversion of output signals could be done in close proximity to the lode cell for the reduction in mixing of noise. Obtained data from the load cell like this manner are transferred to a computer with digital values(of TTL level). To simplify the configuration of a multi-channel DAS, RS-485 communication system has used for data transfer.

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의료비 결정요인 분석을 위한 계량적 모형 고안 (A Quantitative Model for the Projection of Health Expenditure)

  • 김한중;이영두;남정모
    • Journal of Preventive Medicine and Public Health
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    • 제24권1호
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    • pp.29-36
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    • 1991
  • A multiple regression analysis using ordinary least square (OLS) is frequently used for the projection of health expenditure as well as for the identification of factors affecting health care costs. Data for the analysis often have mixed characteristics of time series and cross section. Parameters as a result of OLS estimation, in this case, are no longer the best linear unbiased estimators (BLUE) because the data do not satisfy basic assumptions of regression analysis. The study theoretically examined statistical problems induced when OLS estimation was applied with the time series cross section data. Then both the OLS regression and time series cross section regression (TSCS regression) were applied to the same empirical da. Finally, the difference in parameters between the two estimations were explained through residual analysis.

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시간 의존적인 상품 추천을 위한 지수 평활 시간 연관 규칙 (Exponential Smoothing Temporal Association Rules for Recommendation of Temperal Products)

  • 정경자
    • 한국컴퓨터정보학회논문지
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    • 제10권1호
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    • pp.45-52
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    • 2005
  • 본 연구에서는 시간 연관 규칙에 지수 평활법을 적용한 상품 추천 알고리즘을 제안한다. 시간 연관 규칙은 기존의 연관 규칙에 시간 개념을 적용한 연관 규칙이다. 본 연구에서는 과거 데이터 보다 최신의 데이터에 가중치를 더 부여한 지수 평활 시간 연관 규칙을 제안한다. 제안한 알고리즘은 시간 의존적인 데이터에 적용하여 시뮬레이션을 한 결과 지수 평활법을 적용한 시간 연관 규칙이 기존의 시간 연관 규칙보다 실행시간 면에서 다소 오래 걸리지만 상품 추천 측면에서 더 효과적이다.

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소프트웨어 신뢰모형에 대한 베이지안 접근 (Bayesian Approach for Software Reliability Models)

  • 최기헌
    • Journal of the Korean Data and Information Science Society
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    • 제10권1호
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    • pp.119-133
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    • 1999
  • 마코브체인 몬테칼로 방법을 소프트웨어 신뢰모형에 이용하였다. 베이지안 추론에서 조건부 분포를 가지고 사후분포를 결정하는데 있어서의 계산 문제를 고찰하였다. 특히 레코드값을 통계량을 갖고서 혼합과정과 중첩과정에 대하여 깁스샘플링 알고리즘과 메트로폴리스 알고리즘을 활용하여 베이지안 계산과 모형 선택을 제시하고 모의실험자료를 이용하여 수치적 인 계산을 시행하고 그 결과를 비교하였다.

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소지역 추정을 위한 M-분위수 커널회귀 (M-quantile kernel regression for small area estimation)

  • 심주용;황창하
    • Journal of the Korean Data and Information Science Society
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    • 제23권4호
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    • pp.749-756
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    • 2012
  • 소지역 추정을 위해 널리 사용되고 있는 방법 중 하나는 선형혼합효과모형이다. 그러나 종속변수와 독립변수 사이의 관계가 비선형일 때 이 모형은 소지역 관련 모수에 대해 편의된 추정값을 초래한다. 본 논문에서는 M-분위수 커널회귀를 사용하여 소지역의 평균을 추정하는 방법을 제안한다. 그리고 모의실험을 통하여 서포트벡터분위수회귀와 성능을 비교함으로써 제안된 방법의 우수성을 보인다.

Nonparametric Bayesian methods: a gentle introduction and overview

  • MacEachern, Steven N.
    • Communications for Statistical Applications and Methods
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    • 제23권6호
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    • pp.445-466
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    • 2016
  • Nonparametric Bayesian methods have seen rapid and sustained growth over the past 25 years. We present a gentle introduction to the methods, motivating the methods through the twin perspectives of consistency and false consistency. We then step through the various constructions of the Dirichlet process, outline a number of the basic properties of this process and move on to the mixture of Dirichlet processes model, including a quick discussion of the computational methods used to fit the model. We touch on the main philosophies for nonparametric Bayesian data analysis and then reanalyze a famous data set. The reanalysis illustrates the concept of admissibility through a novel perturbation of the problem and data, showing the benefit of shrinkage estimation and the much greater benefit of nonparametric Bayesian modelling. We conclude with a too-brief survey of fancier nonparametric Bayesian methods.

A Study of the Parameters of the Retention of Monosubstituted Benzenes in Reversed-Phase Liquid Chromatography

  • 이대운;육견성;김호섭;이원
    • Bulletin of the Korean Chemical Society
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    • 제10권1호
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    • pp.34-39
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    • 1989
  • The relationship between the solute retention and physical parameters describing the interaction between the solute and mobile phase was investigated to predict the solute retention easily in RPLC. The retention data of monosubstituted benzenes were measured on the $\mu$-Bondapak C18 and phenyl columns with methanol-water systems. The linear relationship between dielectric increment($\epdilon'$) and retention data was observed. When the solute form hydrogen bonding with solvent molecules, the slope of the ln k' vs. $\epdilon'$ plot is changed as the compositions is varied. The quadric relationship between mixed solvent solubility parameter ($\delta$M) and retention data was observed.

A computational note on maximum likelihood estimation in random effects panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제26권3호
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    • pp.315-323
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    • 2019
  • Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.