• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.95-100
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• 2013

Several observation equipments are being used for determination of the water vapor content and precipitable water vapor (PWV) because the water vapor is highly variable temporally and spatially. In this study, we used GNSS systems such as GPS and GLONASS in standalone and combined modes to compute PWV and validated their accuracy with respect to the results of other water-vapor monitoring systems. The other systems used were radiosonde and microwave radiometer, and the comparisons were convenient because all three systems were collocated at the test site. The differences of PWW were in the range of 0.6-3.4 mm in the mean sense, and their standard deviations were 1.0-3.8 mm. The relatively large difference of GNSS compared with the other two systems were believed to be caused by the fact that the GNSS antenna used in this study was the kind for which the international standard of phase center variations (PCV) calibration is not available. We expect better accuracy of PWV determination and improved availability of it through integrated data processing of GPS/GLONASS when an appropriate antenna with PCV correction model is used.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.45-52
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• 2020

In this paper, we propose an intention to study the purchase of smart music by Chinese consumers. To study the influence of the originality and usefulness of intelligent music products on the purchase intention of Chinese consumers, and to explore how the originality and usefulness of intelligent music products affect the purchase intention. To achieve this goal, 372 questionnaires were collected through the Internet for frequency analysis, factor analysis, confidence analysis and structural equation analysis of data collection, and were carried out by SPSSV22.0 and AMOSV22.0 methods. Research the validation of assumptions in the model to reveal the psychological and behavioral responses of consumers to smart music products. The results show that the originality and usefulness of new products not only directly affect the purchase intention of Chinese consumers, but also indirectly affect their purchase intention by enhancing their attractiveness. The conclusion of this study is of guiding significance for the development of intelligent music product development and marketing strategy.

• Journal of the Korean Geotechnical Society
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• v.36 no.11
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• pp.61-70
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• 2020

In dynamic centrifuge tests, equivalent shear beam (ESB) container minimizes the boundary effect between the soil model and the wall of the container so as to effectively simulate the boundary conditions of real field state. The ESB container at KAIST was evaluated to be performing properly by Lee et al. (2013). However, it is necessary to re-evaluate the performance of ESB container since the ESB container may have deteriorated over time. Thus, the performance of eight-year-old ESB container was re-evaluated through dynamic centrifuge tests. Firstly, the natural period of the empty ESB container was compared with the results of Lee et al. (2013). Then the boundary effect of sand-filled ESB container was evaluated. Results show that the dynamic behavior of the sand-filled ESB container was similar to that of the ground, despite a decrease in the natural period of the empty ESB container over time. In addition, the dynamic response of the ground built in the ESB container and the same ground simulated through numerical analysis with free-field boundary conditions were similar. Therefore, it was found that the boundary effect of the ESB container due to the decrease in the natural period was not significant.

• 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.

• Child Health Nursing Research
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• v.4 no.1
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• pp.5-16
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• 1998

The purpose of nursing education is to prepare the professional pratictioner as nurse who will be interesteed in the health and the related aspects of community and will assume responsibility for con tributing toward the improvement of the health for the all. This means that nursing education must provide opportunities for the development of knowledge, skills, and attitudes which make this possible. Consequently, this approach has relavence for nursing education. Faculty engaged in endless debates about what is to be included, and to what de1th, and what will be given short shrift as a result. Thus, it can be seen why there is so much confusion and lack of agreement between the emphasis and objectives in nursing. This study attempted to review and identify the curriculum content of child nursing in Korea to build and develop the standard curriculum contents for national board examination for nurses and child's health needs for the coming 21st centry. The questionnaire was consisted of items for selection and organization of the knowledge components and type of unit with weigh to be attained in child nursing. Response of 34% of nursing program in university and junior college. Content analysis was done by using consensual validation of essential knowledge for curriculum content to identify what is obvious or trivial. This study pointed out that it is not yet apparent that demographic fact has greatly influenced child nursing curriculum content. In a similar vein the majority of content of child nursing devote little time and weigh to social and epidemically significant to child health. It seems to be needed that the content of child nursing may push the paradigm shift in nursing education such as health promotion and prevention for potentional roles of child and family. In conclusion, it is the time to convoke and debate for convergence of model on essential content and standarization on job analysis for national board exam for nurses in Korea.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.342-350
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• 2016

This study aims to make the stand density management diagram which is very useful for establishing systematic management plan and obtaining management goal in Pinus densiflora forest. To estimate 5 models mainly composed of stand density management diagram, we used total of 1,886 sample plots having more than 75% of the total basal area of the pine trees in each stand. To test the goodness of fit, $X^2$ was computed with a significance level of 5%, and the acceptable error range as 20%. Also standard deviation of the model was $34.59m^3{\cdot}ha^{-1}$, minimum acceptable error range was 16.59% and coefficient of variation was 22.11%. If we use the stand density management diagram, it would be useful to establish the timber yield and thinning plan understanding the pathway of stand density management.

• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.141-150
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• 2008

The response of grain yield(GY) and milled-rice protein content(PC) to crop growth status and nitrogen(N) rates at panicle initiation stage(PIS) is critical information for prescribing topdress N rate at PIS(Npi) for target GY and PC. Three split-split-plot experiments including various N treatments and rice cultivars were conducted in Experimental Farm, Seoul National University, Korea in 2003-2005. Shoot N density(SND, g N in shoot $m^{-2}$) and canopy reflectance were measured before N application at PIS, and GY, PC, and SND were measured at harvest. Data from the first two years(2003-2004) were used for calibrating the predictive models for GY, PC, and SND accumulated from PIS to harvest using SND at PIS and Npi by multiple stepwise regression. After that the calibrated models were used for calculating N requirement at PIS for each of nine plots based on the target PC of 6.8% and the values of SND at PIS that was estimated by canopy reflectance method in the 2005 experiment. The result showed that SND at PIS in combination with Npi were successful to predict GY, PC, and SND from PIS to harvest in the calibration dataset with the coefficients of determination ($R^2$) of 0.87, 0.73, and 0.82 and the relative errors in prediction(REP, %) of 5.5, 4.3, and 21.1%, respectively. In general, the calibrated model equations showed a little lower performance in calculating GY, PC, and SND in the validation dataset(data from 2005) but REP ranging from 3.3% for PC and 13.9% for SND accumulated from PIS to harvest was acceptable. Nitrogen rate prescription treatment(PRT) for the target PC of 6.8% reduced the coefficient of variation in PC from 4.6% in the fixed rate treatment(FRT, 3.6g N $m^{-2}$) to 2.4% in PRT and the average PC of PRT was 6.78%, being very close to the target PC of 6.8%. In addition, PRT increased GY by 42.1 $gm^{-2}$ while Npi increased by 0.63 $gm^{-2}$ compared to the FRT, resulting in high agronomic N-use efficiency of 68.8 kg grain from additional kg N. The high agronomic N-use efficiency might have resulted from the higher response of grain yield to the applied N in the prescribed N rate treatment because N rate was prescribed based on the crop growth and N status of each plot.

• Journal of Gifted/Talented Education
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• v.21 no.4
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• pp.927-943
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• 2011

What are the critical factors in deciding future career to the gifted and talented students? The present study started with this question, and was to develop a career decision-making scale for scientifically gifted undergraduates. For this, literatures related to the scientifically gifted/talent and scientists' career decision-making were reviewed and examined in depth. Based on the review of the related literature, the developed scale of career decision-making was comprised of 26 items in 6 factors, such as individual aptitude & self-realization, economic aspect, work & leisure, familial influence, parents/teachers' recommendation, and experience of science activity during the school days. For the preliminary exploratory factor analysis, 153 undergraduate students who were majoring in natural sciences and engineer participated in the study. For the confirmatory factor analysis, 264 undergraduates who were awarded the presidential scholarships and 93 undergraduates who completed a university-affiliated gifted education center participated. The results of the study are as follows. The fit of measurement model was found to be $x^{2}$=645.157 (df=279, p=.00), TLI=.924, CFI= .935, RMSEA=.061, indicating most of fit indexes were acceptable. Cronbach's ${\alpha}$ in each sub-factor was quite high, .82 for individual aptitude & self-realization, .94 for economic aspect, .84 for work and leisure, .88 for familial influence, .79 for patents/ teachers' recommendation, and .79 for experience of science activity during the school days. The results of the study were discussed whether the developed scale could be used as a valid and reliable tool for measuring career decision-making factors of the scientifically gifted undergraduates in our country.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.2
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• pp.125-130
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• 2015

The objective of this study was to investigate the feasibility of using near infrared spectroscopy (NIRS) to discriminate between grass spices. A combination of NIRS and chemometrics was used to discriminate between Italian ryegrass, perennial ryegrass, and tall fescue seeds. A total of 240 samples were used to develop the best discriminant equation, whereby three spectra range (visible, NIR, and full range) were applied within a 680 nm to 2500 nm wavelength. The calibration equation for the discriminant analysis was developed using partial least square (PLS) regression and discrimination equation (DE) analysis. A PLS discriminant analysis model for the three spectra range that was developed with the mathematic pretreatment "1,8,8,1" successfully discriminated between Italian ryegrass, perennial ryegrass, and tall fescue. An external validation indicated that all of the samples were discriminated correctly. The discriminant accuracy was shown as 68%, 78%, and 73% for Italian ryegrass, perennial ryegrass, and tall fescue, respectively, with the NIR full-range spectra. The results demonstrate the usefulness of the NIRS-chemometrics combination as a rapid method for the discrimination of grass species by seed.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1179-1194
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• 2020

This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R² (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R² = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.