• Title/Summary/Keyword: method validation #5

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Estimation of Evapotranspiration with SEBAL Model in the Geumgang Upper Basin, Korea (SEBAL모형을 이용한 증발산량의 추정 금강 상류지역을 대상으로)

  • 유진웅
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.517-522
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    • 2003
  • Exact estimation of evapotranspiration is important to understand natural phenomena and social issues associated with the climate such as irrigation scheme, reservoir water management, and many other meteorological and climatological problems. To overcome limits of point measurement of evapotranspiration, several models have been developed through the techniques of remote sensing and Geographical Information System. SEBAL model is one of them, based on the energy balance equation, and it has a lot of advantages such as that it requires relatively small empirical relations. In this study, the SEBAL model has been calibrated and validated in Geumgang upper basin, Bochung-stream basin, Korea with 5 satellite images Landsat 5 TM. In validation, the results of SEBAL model were compared with those by Merton method. After validation, the spatial and temporal characteristics of the distribution of evapotranspiration within the basin were analyzed with 3 factors, the aspect of slope, the angle of slope, and the land cover.

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Infrared Rainfall Estimates Using the Probability Matching Method Applied to Coincident SSM/I and GMS-5 Data

  • Oh, Hyun-Jong;Sohn, Byung-Ju;Chung, Hyo-Sang
    • Proceedings of the KSRS Conference
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    • 1999.11a
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    • pp.117-121
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    • 1999
  • Relations between GMS-5 infrared brightness temperature with SSM/I retrieved rain rate are determined by a probability matching method similar to Atlas et al. and Crosson et al. For this study, coincident data sets of the GMS-5 infrared measurements and SSM/I data during two summer seasons of 1997 and 1998 are constructed. The cumulative density functions (CDFs) of infrared brightness temperature and rain rate are matched at pairs of two variables which give the same percentile contribution. The method was applied for estimating rain rate on 31 July 1998, examining heavy rainfall estimation of a flash flood event over Mt. Jiri. Results were compared with surface gauge observations run by Korean Meteorological Administration. It was noted that the method produced reasonably good quality of rain estimate, however, there was large area giving false rain due to the anvil type clouds surrounding deep convective clouds. Extensive validation against surface rain observation is currently under investigation.

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Validation of Nursing Care Sensitive Outcomes related to Knowledge (지식에 관한 간호결과도구의 타당성 조사)

  • 이은주
    • Journal of Korean Academy of Nursing
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    • v.33 no.5
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    • pp.625-632
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    • 2003
  • Purpose: The purpose of this study was to assess the importance and sensitivity to nursing interventions of four nursing sensitive nursing outcomes selected from the Nursing Outcomes Classification (NOC). Outcomes for this study were 'Knowledge: Diet', 'Knowledge: Disease Process', 'Knowledge: Energy Conservation', and 'Knowledge: Health Behaviors'. Method: Data were collected from 183 nurses working in 2 university hospitals. Fehring method was used to estimate outcome and indicators' content and sensitivity validity. Multiple and stepwise regression were used to evaluate relationships between each outcome and its indicators. Result: Results confirmed the importance and nursing sensitivity of outcomes and their indicators. Key indicators of each outcomes were found by multiple regression. 'Knowledge: Diet' was suggested for adding new indicators because the variance explained by indicators was relatively low. Not all of the indicators selected for stepwise regression model were rated for highly in Fehring method. The R² statistics of the stepwise regression models were between 18 and 63% in importance by selected indicators and between 34 and 68% in contribution by selected indicators. Conclusion: This study refined what outcomes and indicators will be useful in clinical practice. Further research will be required for the revision of outcome and indicators of NOC. However, this study refined what outcomes and indicators will be useful in clinical practice.

Validation of Kinetic Method for the PKA Assay in Plasma-Derived Products

  • Shin, In-Soo;Hong, Choong-Man;Koh, Hyun-Chul;Hong, Seung-Hwa
    • Biomolecules & Therapeutics
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    • v.13 no.1
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    • pp.59-63
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    • 2005
  • A kinetic assay was carried out in order to compare the ability of detection for prekallikrein activator(PKA) in plasma-derived products with that of an endpoint assay and a commercial method. Using these methods, 9 human albumin preparations were assayed and compared to each other. The coefficient of variation between the Kinetic assay and the end point assay was found within 6.6% and this result showed that two methods were highly correlative and the end point assay could act as a replacement of the kinetic assay. Another important goal of this study was to investigate the reproducibility among laboratories on the kinetic assay. A collaborative study was performed to validate the kinetic method with intra and inter assays. The coefficient of variation for the intra assay of each laboratory was less than 4% and that for between individuals in the inter assay was 4.1%. These results revealed that the kinetic assay showed good reproducibility. The contents of PKA in plasma-derived products were also determined by the kinetic assay. As a result, it was found that trace amounts of PKA were present in 32 human immunoglobulin preparations, however the average concentration of PKA in 171 albumin preparations was 5.8 IU/mL.

Validity and Reliability of an Instrument for Predictive Nursing Intention for SARS Patient Care (SARS 환자간호 의도예측 도구의 타당도 및 신뢰도 검증 연구)

  • Yoo, Hye Ra;Kwon, Bo Eun;Jang, Yon Soo;Youn, Heun Keung
    • Journal of Korean Academy of Nursing
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    • v.35 no.6
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    • pp.1063-1071
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    • 2005
  • Purpose: This study was done to develop and test validity and reliability of on instrument for predicting nursing intention for SARS patient care. Method: The psychometric properties of a SARS patient care attrition prediction tool, based on the Theory of Planned Behavior, were examined in this study. The Three-phase design involved a) salient beliefs generated from clinical nurses (n=43) b) content validation by expert panel evaluations(n=5) c) face validation by plot testing (n=10) d) and instrument validation in a cross sectional survey (n=299). Psychometric analysis of survey data provided empirical evidence of the construct validity and reliability of the instrument. Result: Principal component analysis verified the hypothesized 6-factor solution, explaining $68.2\%$ of variance, and Alpha coefficients of .7538 to .9389 indicated a high internal consistency of the instrument. Conclusion: The instrument can be used by nurse administrators and researcher to assess clinical nurses' salient beliefs about caring for SARS patients, guide tailored intervention strategies to effective caring, and evaluate the effectiveness of interventions.

Validation and Determination of the Contents of Acetaldehyde and Formaldehyde in Foods

  • Jeong, Hye-Seung;Chung, Hyun;Song, Sang-Hoon;Kim, Cho-Il;Lee, Joon-Goo;Kim, Young-Suk
    • Toxicological Research
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    • v.31 no.3
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    • pp.273-278
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    • 2015
  • The aim of this study was to develop an efficient quantitative method for the determination of acetaldehyde (AA) and formaldehyde (FA) contents in solid and liquid food matrices. The determination of those compounds was validated and performed using gas chromatography-mass spectrometry combined by solid phase micro-extraction after derivatization with O-(2,3,4,5,6-pentafluoro-benzyl)-hydroxylamine hydrochloride. Validation was carried out in terms of limit of detection, limit of quantitation, linearity, precision, and recovery. Then their contents were analyzed in various food samples including 15 fruits, 22 milk products, 31 alcohol-free beverages, and 13 alcoholic beverages. The highest contents of AA and FA were determined in a white wine (40,607.02 ng/g) and an instant coffee (1,522.46 ng/g), respectively.

Studies on 5 Protein Fractions Prediction of Forage Legume Mixture by NIRS

  • Lee, Hyo-Won;Jang, Sungkwon;Lee, Hyo-Jin;Park, Hyung-Soo
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.34 no.3
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    • pp.214-218
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    • 2014
  • This study was conducted to assess the feasibility of near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for the estimation of crude protein (CP) fractions in forage legume mixtures (sudangrass and pea mixture, and kidney bean and potato mixture). A total of 178 samples were collected and their spectral reflectance obtained in the range of 400~2,500 nm. Of these, 50 samples were selected for calibration and validation, and 35 samples were used for calibration of the data set, and the modified partial least square regression (MPLSR) analysis was performed. The correlation coefficient ($r^2$) and the standard error of cross-validation (SECV) of the calibration models in the CP fractions, A, B1, B2, B3, and C, were 0.94 (1.05), 0.92 (0.74), 0.96 (0.95), 0.91 (0.42), and 0.83 (0.38), respectively. Fifteen samples were used for equation validation, and the $r^2$ and the standard error of prediction (SEP) were 0.87 (1.45), 0.91 (0.49), 0.94 (1.13), 0.36 (0.96), and 0.74 (0.67), respectively. This study showed that NIRS could be an effective tool for the rapid and precise estimation of CP fractions in forage legume mixtures.

Determination of Seed Lipid and Protein Contents in Perilla and Peanut by Near-Infrared Reflectance Spectroscopy

  • Oh, Ki-Won;Choung, Myoung-Gyun;Pae, Suk-Bok;Jung, Chan-Sik;Kim, Byung-Joo;Kwon, Yil-Chan;Kim, Jung-Tae;Kwack, Yong-Ho
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.45 no.5
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    • pp.339-342
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    • 2000
  • Near-infrared reflectance spectroscopy (NIRS) was used to estimate the lipid and protein contents in ground seed samples of perilla (Perilla frutescens Brit.) and peanut (Arachis hypogaea L.). A total of 46 perilla and 80 peanut calibration samples and 23 perilla and 46 pea. nut NIRS validation samples were used for NIRS equation development and validation, respectively. Validation of these NIRS equations showed a range of very low bias (-0.05 to 0.13 %) and standard error of prediction corrected for bias (0.224 to 0.803%) and very high coefficient of determination ($R^2$) (0.962 to 0.985). It was concluded that NIRS could be adapted as a mass screening method for lipid and protein contents in perilla and peanut seed.

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Development of TREND dynamics code for molten salt reactors

  • Yu, Wen;Ruan, Jian;He, Long;Kendrick, James;Zou, Yang;Xu, Hongjie
    • Nuclear Engineering and Technology
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    • v.53 no.2
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    • pp.455-465
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    • 2021
  • The Molten Salt Reactor (MSR), one of the six advanced reactor types of the 4th generation nuclear energy systems, has many impressive features including economic advantages, inherent safety and nuclear non-proliferation. This paper introduces a system analysis code named TREND, which is developed and used for the steady and transient simulation of MSRs. The TREND code calculates the distributions of pressure, velocity and temperature of single-phase flows by solving the conservation equations of mass, momentum and energy, along with a fluid state equation. Heat structures coupled with the fluid dynamics model is sufficient to meet the demands of modeling MSR system-level thermal-hydraulics. The core power is based on the point reactor neutron kinetics model calculated by the typical Runge-Kutta method. An incremental PID controller is inserted to adjust the operation behaviors. The verification and validation of the TREND code have been carried out in two aspects: detailed code-to-code comparison with established thermal-hydraulic system codes such as RELAP5, and validation with the experimental data from MSRE and the CIET facility (the University of California, Berkeley's Compact Integral Effects Test facility).The results indicate that TREND can be used in analyzing the transient behaviors of MSRs and will be improved by validating with more experimental results with the support of SINAP.

Exploring Machine Learning Classifiers for Breast Cancer Classification

  • Inayatul Haq;Tehseen Mazhar;Hinna Hafeez;Najib Ullah;Fatma Mallek;Habib Hamam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.4
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    • pp.860-880
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    • 2024
  • Breast cancer is a major health concern affecting women and men globally. Early detection and accurate classification of breast cancer are vital for effective treatment and survival of patients. This study addresses the challenge of accurately classifying breast tumors using machine learning classifiers such as MLP, AdaBoostM1, logit Boost, Bayes Net, and the J48 decision tree. The research uses a dataset available publicly on GitHub to assess the classifiers' performance and differentiate between the occurrence and non-occurrence of breast cancer. The study compares the 10-fold and 5-fold cross-validation effectiveness, showing that 10-fold cross-validation provides superior results. Also, it examines the impact of varying split percentages, with a 66% split yielding the best performance. This shows the importance of selecting appropriate validation techniques for machine learning-based breast tumor classification. The results also indicate that the J48 decision tree method is the most accurate classifier, providing valuable insights for developing predictive models for cancer diagnosis and advancing computational medical research.