• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.43-52
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• 2024

Recent abnormal climate conditions have increased the risk of slope collapses, which frequently result in significant loss of life and property due to the absence of early prediction and warning dissemination. In this paper, we develop a slope condition analysis system using IoT sensors and AI-based camera to assess the condition of slopes. To develop the system, we conducted hardware and firmware design for measurement sensors considering the ground conditions of slopes, designed AI-based image analysis algorithms, and developed prediction and warning solutions and systems. We aimed to minimize errors in sensor data through the integration of IoT sensor data and AI camera image analysis, ultimately enhancing the reliability of the data. Additionally, we evaluated the accuracy (reliability) by applying it to actual slopes. As a result, sensor measurement errors were maintained within 0.1°, and the data transmission rate exceeded 95%. Moreover, the AI-based image analysis system demonstrated nighttime partial recognition rates of over 99%, indicating excellent performance even in low-light conditions. Through this research, it is anticipated that the analysis of slope conditions and smart maintenance management in various fields of Social Overhead Capital (SOC) facilities can be applied.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.244-250
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• 2007

Membrane inlet mass spectrometer (MIMS) has been used to accurately quantify dissolved gases in liquid samples. In this study, the MIMS system was applied to measure dissolved methane in seawater and sediment porewater. To evaluate the accuracy of the measurement, liquid samples saturated with different methane partial pressure were prepared and the methane concentrations were quantified with the MIMS system. The measured values correspond well with the expected values calculated from solubility constants. The standard error of the measurements were $0.13{\sim}0.9%$ of the mean values. The distribution of dissolved methane concentration in seawater of the South Sea of Korea revealed that the physical parameters primarily control the methane concentration in sea water. The MIMS system was effective to resolve the small dissolved methane difference among water masses. The probe type inlet in MIMS system was proven to be effective to measure porewater methane concentration.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.298-310
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• 2007

Intercomparison between eight radiative transfer codes used for the studies of COMS (Communications, Ocean, and Meteorological Satellite) in Korea was performed under pure molecular, i.e., Rayleigh atmospheres in four shortwave fluxes: 1) direct solar irradiance at the surface, 2) diffuse irradiance at the surface, 3) diffuse upward flux at the surface, and 4) diffuse upward flux at the top of the atmosphere. The result (hereafter called the H15) from Halthore et al.'s study (2005) which intercompared and averaged 15 codes was used as a benchmark to examine the COMS models. Uncertainty of the seven COMS models except STREAMER was ${\pm}4%$ with respect to the H15, comparable with ${\pm}3%$ of Halthore et al.'s (2005). The uncertainty increased under a large $SZA=75^{\circ}$. The SBDART model generally agreed with the H15 better than the 6S model, but both models in the shortwave infrared region were equally good. The direct solar irradiance fluxes at the surface, computed by the SBDARTs of four different users, were different showing a relative error of 1.4% $(12.1Wm^{-2})$. This reason was partially due to differently installing the wavelength resolution in the flux integration. This study may be useful for selecting the optimum model in the shortwave region.

• Journal of Korean Society of Forest Science
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• v.13 no.1
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• pp.79-84
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• 1971

This study is, by correlation and regression analysis, on the correlation between culm height and other growth factors which are circle at eye height and length of internode. The samples were come by in Tamyang district, To sum up, the results are as follows; 1. Two growth factors are much more correlative to culm height; both simple correlation and multiple correlation between the former and the latter are significant. ($r_{yx}=0.91$, $r_{yz}=0.78$, $r_{yx{\cdot}z}=0.84$, $r_{yz{\cdot}x}=0.55$, $R_{y{\cdot}xz}=0.94$) Seeing above significance, circle at eye height is more highly correlative than length of internode. 2. The following regression equation was derived from regression analysis. y= -0.687+0.335x+0.206z. y ; culm height. x ; circle at eye height. z ; length of internode. 3. By testing of the equation, regression coefficients are as follows; ${\beta}{\neq}O$, ${\gamma}{\neq}O$, ${\beta}{\neq}O{\neq}{\gamma}$ 4. The results tested the precision of the empirical formula, standard error of standard error by percentage are as follows. $Sy{\cdot}xz=0.89$, $Sy{\cdot}xz(%)=8.14$.

• Journal of The Korean Society of Grassland and Forage Science
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• v.26 no.1
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• pp.53-62
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• 2006

Near infrared reflectance spectroscopy (NIRS) has been increasingly used as a rapid, accurate method of evaluating some chemical compositions in forages. Analysis of forage quality by NIRS usually involves dry ground samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations and spectral math treatments on prediction ability of chemical composition for corn silage by NIRS. A population of 112 corn silage representing a wide range in chemical parameters were used in this investigation. Samples of com silage were scanned at 2nm intervals over the wavelength range 400-2500nm and the optical data recorded as log l/Reflectance(log l/R) and scanned in overt-dried grinding(ODG), liquid nitrogen grinding(LNG) or intact fresh(IF) condition. Samples were analysed for neutral detergent fiber(NDF), acid detergent fiber(ADF), acid detergent lignin(ADL), crude protein(CP) and crude ash content were expressed on a dry-matter(DM) basis. The spectral data were regressed against a range of chemical parameters using modified partial least squares(MPLS) multivariate analysis in conjunction with four spectral math treatments to reduce the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation(SECV). The results of this study show that NIRS predicted the chemical parameters with very high degree of accuracy(the correlation coefficient of cross validation$(R^2cv)$ range from $0.70{\sim}0.95$) in ODG. The optimum equations were selected on the basis of minimizing the standard error of prediction(SEP). The Optimum sample preparation methods and spectral math treatment were for ADF, the ODG method using 2,10,5 math treatment(SEP = 0.99, $R^2v=0.93$), and for CP, the ODG method using 1,4,4 math treatment(SEP = 0.29. $R^2v=0.91$).

• Korean Journal of Poultry Science
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• v.15 no.3
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• pp.211-218
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• 1988

Data on egg number from time of first lay to 71 week of age were obtained from samples of single comb white leghorn breeder and brown layer breeder populations which were raised at manny breeding Co. These data were used to estimate the heritabilities of age at sexual maturity, early egg number, residual egg number and annual egg number. Also, the genetic correlation coefficients between these traits were estimated and selection efficiencies of each segment in early part record were estimated by use of the heritabilities and generic correlations. The estimated heritabilities and standard errors in two lines(W and B) were $0.30\pm0.07$ and $0.33\pm0.08$ at early records, $0.19\pm0.06$ and $0.18\pm$0.05 at residual records and $0.37\pm0.09$ and $0.49\pm0.10$ at time of first lay. Those at annual records were $0.24\pm0.06$ equally. The estimated correlation coefficients and standard errors between early record and annual record were $0.76\pm0.08$ and $0.77\pm0.07$. Those between early record and residual record were $0.46\pm0.15$ and $0.39\pm0.16$ respectively. At improving annual egg production per year, selection based on early part record(SM to 40 week of age) would be 69% more efficient than on annual record in line W and 80% more efficient than on annual record in line B. But, if it were considered that egg weight decreased due to sexual maturity and cost for data collection, use of selected segment from 35~40week of age in line W and from 31~40 week of age in line B would be desired in spite of a. small loss in relative selection efficiency. The generation interval would not be shortened.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.25-30
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• 2013

Purpose: To evaluate kidney function, renal relative uptake is very important and is affected by kidney and the setting of background region of interest (ROI). In particular, in the case of patients with hydronephrosis to the naked eyes, such as size, position and shape etc. can be difficult to identify. So according to ROI to be set by user, the results are many differences. This study assumes the ROI of a constant kidney. According to the change of background ROI by analyzing renal relative uptake affect how the results are intended to study. Materials and Methods: From January 2012 to February 2013, we analyzed 27 patients with hydronephrosis who were examined MAG3 test in nuclear medicine department of Samsung medical center. After patients were received intravenous injection of $^{99m}Tc-MAG3$ 185 MBq (5 mCi) data were obtained. While we reconstructed images of patients, we've changed background ROI in the process of setting up ROI. First, in the process of renal processing, automatic ROI which set automatically and background ROI which needed to set manually were compared. Second, we set the ROI position separated by above, lateral and bottom of kidney. Third, background setting time were compared with 1-2 min and 2-3 min. Results: The relative uptake occurred in 3.7%p of the errors on average in Automatic & Manual ROI study. And comparison of background ROI position study, located in the lower position was more accurate results. Above, lateral, bottom each of the values 74.6%, 67.6% and 62.0% showed respectively. The standard value was 59.9%. finally, split function range test doesn't show significant difference. Conclusion: The study shows that relative uptake of kidney is affected in the background ROI. Therefore, it should be set by considering various dependent factors.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Korean Journal of Food Science and Technology
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• v.36 no.5
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• pp.701-710
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• 2004

Uncertainty was quantified to evaluate calcium determination result in infant formula with AAS (Atomic Absorption Spectrometry) and ICP-AES (Inductively Coupled Plasma-Atomic Emission Spectrometry). Uncertainty sources in measurand, such as sample weight, final volume of sample, sample dilution and the instrumental result were identified and used as parameters for combined standard uncertainty based on the GUM (Guide to the expression of uncertainty in measurement) and Draft EURACHEM/CITAC Guide. Uncertainty components of each sources in measurand were identified as resolution, reproducibility and stability of chemical balance, standard material purity, standard material molecular weight, standard solution concentration, standard solution dilution factor, sample dilution factor, calibration curve, recovery, instrumental precision, reproducibility, and stability, Each uncertainty components were evaluated by uncertainty types and included to calculate combined uncertainty. The kinds of uncertainty sources and components in the analytical method by AAS and ICP-AES were same except sample dilution factor for AAS. The analytical results and combined standard uncertainties of calcium content were estimated within the certification range $(367{\pm}20\;mg/100g)$ of CRM (Certified Reference Material) and were not significantly different between method by AAS followed by ashing and method by ICP-AES followed by acid digestion as $359.52{\pm}23.61\;mg/100g\;and\;354.75{\pm}16.16\;mg/100g$, respectively. Identifying uncertainty sources related with precision, repeatability, stability, and maintaining proper instrumental conditions as well as personal proficiency was needed to reduce analytical error.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.