• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.975-984
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• 2019

As an essential prerequisite for systematic and integrated management of river water, it is necessary to secure the basic data such as discharge supplied to the river and released from the river. Under the current permit system for river water use, 59.1% of licensed facilities were found to have no discharge meters in 2017, especially for agricultural water, which makes it difficult to secure reliable data as a large portion of the reports are voluntarily reported by users. In this study, the indirect discharge measurement method of calculating the discharge through the power usage of the pumping station was applied to secure reliable discharge data. In particular, focusing on the fact that the discharge calculated by the power usage method differed with the actual discharge according to the level of the river, the study was conducted on improving the power usage method reflecting the river water level and improving the accuracy of discharge data. Analysis of the discharge calculated using the power usage method considering river water level using the correlation analysis method such as regression analysis, percent difference, root mean square error etc. confirmed that the results are not high compared to the conventional power usage method, but are slightly more approximated to the actual discharge. Therefore, although reliable discharge data can be obtained from the existing power usage method, it is expected that more accurate data on intaking water of river water can be obtained if the improved power usage method is used at points where the variation in the water level of the river is large.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.677-685
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• 2007

The objective of this study is to evaluate the applicability of multi-objective genetic algorithm(MOGA) in order to calibrate the parameters of conceptual rainfall-runoff model, Tank model. NSGA-II, one of the most imitating MOGA implementations, is combined with Tank model and four multi-objective functions such as to minimize volume error, root mean square error (RMSE), high flow RMSE, and low flow RMSE are used. When NSGA-II is employed with more than three multi-objective functions, a number of Pareto-optimal solutions usually becomes too large. Therefore, selecting several preferred Pareto-optimal solutions is essential for stakeholder, and preference-ordering approach is used in this study for the sake of getting the best preferred Pareto-optimal solutions. Sensitivity analysis is performed to examine the effect of initial genetic parameters, which are generation number and Population size, to the performance of NSGA-II for searching the proper paramters for Tank model, and the result suggests that the generation number is 900 and the population size is 1000 for this study.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2111-2111
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• 2001

A chemoinfometrical method for evaluating the quantitative determination of crystallinity one polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the and compared with the conventional powder X-ray diffraction method was performed. [Method] The pPure a and g forms of indomethacin (IMC) were prepared by reportedusing published methods. Six kinds of standard samples obtained by physically mixing of a and g forms. After the powder X-ray diffraction profiles of samples have been measured, the intensity values were normalized to against the intensity of silicon powder as the as an external standard. The calibration curves for quantification of crystal content were based upon the total relative intensity of four diffraction peaks from of the form g crystal. FT-NIR spectra of six calibration sample sets were recorded 5 times with the NIR spectrometer (BRAN+LUEBBE). Chemoinfometric analysis was performed on the NIR spectral data sets by applying the principal component regression (PCR). [Results] The relation between the actual and predicted polymorphic contents of form g IMC measured using by the X-ray diffraction method shows a good straight linen linear relation., and it has slope of 0.023, an intercept of 0.131 and a correlation coefficient of 0.986. PCR analyses wereis was performed based on normalized NIR spectra sets offer standard samples of known content of IMC g form. IMC. A calibration equation was determined to minimize the root mean square error of the predictionthe prediction. Figure 1 shows a plot of the calibration data obtained by NIR method between the actual and predicted contents of form g IMC. The predicted values were reproducible and had a smaller standard deviation. Figure 2 shows that the plot for the predicted transformation rate (%) of form a IMC to form g as measured by X-ray diffractomeoy against to those as measured by NIR method. The plot has a slope of 1.296, an intercept of 1,109, and a correlation coefficient of 0.992. The line represents a satisfactory correlation between the two predicted values of form g IMC content. Thus NIR spectroscopy is an effective method for the evaluation to the pharmaceutical products of quantitative of polymorph.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.11
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• pp.1445-1454
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• 2010

Two separate animal trials were conducted to evaluate the coincidence of dry matter intake (DMI) and average daily gain (ADG) predicted by the Cornell Net Carbohydrate and Protein System (CNCPS) and observed actually in crossbred growing bulls kept in a traditionally confined feeding system in China. In Trial 1, 45 growing Simmental${\times}$Mongolia crossbred F1 bulls were assigned to three treatments (T1-3) with 15 animals in each treatment. Trial 2 was conducted with 60 Limousin${\times}$Fuzhou crossbred F2 bulls allocated to 4 treatments (t1-4). All of the animals were confined in individual stalls. DMI and ADG for each bull were measured as a mean of each treatment. All of the data about animals, environment, management and feeds required by the CNCPS model were collected, and model predictions were generated for animals on each treatment. Subsequently, model-predicted DMI and ADG were compared with the actually recorded results. In the three treatments in Trial 1, 93.3, 80.0 and 73.3% of points fell within the range from -0.4 to 0.4 kg/d for DMI mean bias; similarly, in the four treatments in Trial 2, about 86.7, 73.3, 73.3 and 80.0% of points fell within the same range. These results indicate that the CNCPS model can accurately predict DMI of crossbred bulls in the traditionally confined feeding system in China. There were no significant differences between predicted and observed ADG for T1 (p = 0.06) and T2 (p = 0.09) in Trial 1, and for t1 (p = 0.07), t2 (p = 0.14) and t4 (p = 0.83) in Trial 2. However, significant differences between predicted and observed ADG values were observed for T3 in Trial 1 (p<0.01) and for t3 in Trial 2 (p = 0.04). By regression analysis, a statistically different value of intercept from zero for the regression equation of DMI (p<0.01) or an identical value of ADG (p = 0.06) were obtained, whereas the slopes were significantly different (p<0.01) from unity for both DMI and ADG. Additionally, small root mean square error (RMSE) values were obtained for the unbiased estimator of the two variances (DMI and ADG). Thus, the present results indicated that the CNCPS model can give acceptable estimates of DMI and ADG of crossbred growing bulls kept in a traditionally confined feeding system in China.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.5 no.2
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• pp.61-72
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• 2007

INTRODUCTION: Local heat and cold application has been frequently used as means of muscle relaxation and blood circulation or reinforcing muscle strength, relaxing muscle tension in clinical situation. In particular, it has been known that long-term heat and cold application for relaxing muscle tension inhibits muscle spasticity or tension. But, it has been rarely reported that what influences of heat and cold application on activation of muscle action potential. Therefore, this study aims to analyze surface temperature and electromyography activities according to the heat and cold application. METHODE: Subjects of this research were 10 normal men and women (5 men, 5 women). Hot pack and cold pack was applied to vastus medialis muscle of thigh and rectus femoris muscle for 20 min. Surface temperature of vastus medialis muscle and rectus femoris muscle was measured, knee joint of subjects was in $45^{\circ}$ flexion, sitting on a chair, maximal isometric contraction was induced, surface electromyography (sEMG) signals were collected and root mean square (RMS) and median frequency (MOF) were analyzed. All measurements were conducted before and immediately after experiment, 10 min., 20 min. and 30 min. after experiment. Data were analyzed with SPSS 12.0 program, comparison of changes in superficial temperature and sEMG signals through repeated measurement was conducted with repeated measures ANOVA and significance level $\alpha$ was 0.05. RESULTS: Changes of surface temperature of vastus medialis muscle according to cold application were radically decreased immediately after application, but it was recovered after 30 min. of application and it showed significant difference (F4. 36=72.216, P<0.001). Surface temperature of rectus femoris also showed radical decrease immediately after application, but it was recovered after 30 min. of application and showed significant difference (F4. 36=88.930, P<0.001). Changes of surface temperature of vastus medialis muscle according to heat application were radically increased immediately after application, but it was recovered after 30 min. of application and it showed significant difference (F4. 36=27.267, P<0.001). Surface temperature of rectus femoris also showed radical decrease immediately after application, but it was recovered after 30 min. of application and showed significant difference (F4. 36=19.774, P<0.001). Changes of sEMG by heat and cold application were no statistical difference. Surface temperature of skeletal muscle after heat and cold application showed significant change for 30 min., but it was found that increase or decrease of surface temperature had not great influence on sEMG activities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.962-969
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• 2013

This study used Computational Fluid Dynamics(CFD) to assess the properties of the air current inflow and the flow velocity distribution in the fume hood. In order to verify the effect of improvement, it was also predicted the characteristics of the flow pattern in case the hood face is structurally improved. The assessment of the capture velocity with the existing fume hood confirmed maximum 23 to 30% difference as compared to the root mean square (RMS). And the hood face showed great difference in flow velocity, with the flow velocity in the upper part is 58 to 68% faster than that in the lower part of the hood. So, as a result of the improvement of the hood designed to maintain a steady exhaust at the hood face (that is, installing a baffle on the inner wall and designing the slot type face), a difference of maximum 7% as compared to RMS appeared while maximum 12% differentiation in flow velocity through sections was predicted, showing mitigation of much of the difference in control velocity as compared to the previous structure.

• Atmosphere
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• v.24 no.3
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• pp.391-402
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• 2014

This study investigated the performances of precipitable water vapor (PWV) retrieval from the sets of ground global positioning system (GPS) signals, each of which had different length of observing-session duration, for the purpose of obtaining as short session duration as possible that is required at the least for appropriate retrieval of the PWV for meteorological usage. The shorter duration is highly desirable to make the most use of the GPS instrument on board the mobile observation vehicle making measurements place by place. First, using Bernese 5.0 software the PWV retrieval was conducted with the data sets of GPS signals archived continuously in 30 seconds interval during 2-month period of January and February, 2012 at Bukgangneung site. Each of the PWVs produced independently using different session durations was compared to that of radio-sonde launched at the same GPS location, a Bukgangneung site. Second, the same procedure was done using the data sets obtained from the mobile observation vehicle that was operating at Boseong area in Jeonnam province during Changma observation campaign in 2013, and the results were compared to that at Bukgangneung site. The results showed that as the observing-session duration increased the retrieval errors decreased with the dramatic change happening between 3 and 4 hours of the duration. On average, the root mean square error (RMSE) of the retrieved PWV was around 1 mm for the durations of greater than 4 hours. The results at both the Bukgangneung (fixed site) and Boseong (mobile vehicle) seemed to be fairly comparable with each other. From this study it is believed that at least 4 hours of observing-session duration is needed for the retrieval of PWV from the ground GPS for meteorological usage using Bernese 5.0 software.

• Atmosphere
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• v.28 no.1
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• pp.99-112
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• 2018

In this study, the accuracy of ocean analysis data, which are produced from the Korea Meteorological Administration (KMA) Nucleus for European Modelling of the Ocean/Variational Data Assimilation (NEMO/NEMOVAR, hereafter NEMO) system and the HYbrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation (HYCOM/NCODA, hereafter HYCOM) system, was evaluated using various oceanic observation data from March 2015 to February 2016. The evaluation was made for oceanic thermal environments in the tropical Pacific, the western North Pacific, and the Korean peninsula. NEMO generally outperformed HYCOM in the three regions. Particularly, in the tropical Pacific, the RMSEs (Root Mean Square Errors) of NEMO for both the sea surface temperature and vertical water temperature profile were about 50% smaller than those of HYCOM. In the western North Pacific, in which the observational data were not used for data assimilation, the RMSE of NEMO profiles up to 1000 m ($0.49^{\circ}C$) was much lower than that of HYCOM ($0.73^{\circ}C$). Around the Korean peninsula, the difference in RMSE between the two models was small (NEMO, $0.61^{\circ}C$; HYCOM, $0.72^{\circ}C$), in which their errors show relatively big in the winter and small in the summer. The differences reported here in the accuracy between NEMO and HYCOM for the thermal environments may be attributed to horizontal and vertical resolutions of the models, vertical coordinate and mixing scheme, data quality control system, data used for data assimilation, and atmosphere forcing. The present results can be used as a basic data to evaluate the accuracy of NEMO, before it becomes the operational model of the KMA providing real-time ocean analysis and prediction data.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.155-169
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• 2016

In this study, we developed a multi-sensor blending short-term rainfall forecasting technique using radar and satellite data during extreme rainfall occurrences in Busan and Gyeongnam region in August 2014. The Tropical Z-R relationship ($Z=32R^{1.65}$) has applied as a optimal radar Z-R relation, which is confirmed that the accuracy is improved during 20mm/h heavy rainfall. In addition, the multi-sensor blending technique has applied using radar and COMS (Communication, Ocean and Meteorological Satellite) data for quantitative precipitation estimation. The very-short-term rainfall forecasting performance was improved in 60 mm/h or more of the strong heavy rainfall events by multi-sensor blending. AWS (Automatic Weather System) and MAPLE data were used for verification of rainfall prediction accuracy. The results have ensured about 50% or more in accuracy of heavy rainfall prediction for 1-hour before rainfall prediction, which are correlations of 10-minute lead time have 0.80 to 0.53, and root mean square errors have 3.99 mm/h to 6.43 mm/h. Through this study, utilizing of multi-sensor blending techniques using radar and satellite data are possible to provide that would be more reliable very-short-term rainfall forecasting data. Further we need ongoing case studies and prediction and estimation of quantitative precipitation by multi-sensor blending is required as well as improving the satellite rainfall estimation algorithm.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.107-120
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• 2011

Several MODIS AQUA products have been compared with shipboard data to assess the possibility of using remote sensing to estimate particulate organic carbon (POC) concentration in the surface waters of the East Sea. A total of 30 POC profiles obtained in spring and summer seasons of the years of 2006~2010 were compared with remote sensing reflectance at various wavelengths and diffuse attenuation coefficient at 490 nm observed by MODIS AQUA. The algorithm thus established was $POC=266.85^*[R_{rs}(488)/R_{rs}(555)]^{-1.447}$ ($R^2=0.924$) with root mean square error of 20.9 mg $m^{-3}$. Remotely sensed POC contents derived using our algorithm appeared also not to be affected by the presence of non-POC component in suspended particulate matter. Therefore this algorithm could be applied to obtain POC concentration over the East Sea using MODIS Aqua observation.