• Journal of the Korean earth science society
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• v.34 no.7
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• pp.626-632
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• 2013

In this study the GPS Precipitable Water Vapor (PWV) was derived and evaluated by a radiosode measure during the winter intensive observation in Gangneung site from January 5 till February 29 in 2012. Bernise 5.0 software was used to derive the GPS data. GPS-derived PWV from Zero difference (GANG) and Single difference (GANG and DAEJ) was high variance in time and about 5 times the PWV of radiosonde. GPS post-processing has been performed from two additional IGS site (Xian Dao, Ibaraki-ken) in order to correct the absolute troposphere errors. As a result, the mean bias error (MBE) and root mean square error (RMSE) and correlation compared with radiosonde measure were 0.67 mm, 6.40 mm, and 0.93, respectively. In order to correct the relative troposphere errors from the altitudinal difference between the two GPS receivers, we calculated the GPS-derived PWV by adding the data of GPS that was installed in Gangneung-Wonju University near the Gangwon Regional Meteorological Administration. In the end, the improved result showed that MBE, RMSE and correlation in comparison with radiosonde measures were 0.61 mm, 5.79 mm, and 0.93, respectively.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.280-289
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• 2008

An extensive set of both in-situ and satellite data regarding oceanic sea surface temperatures in Northeast Asian seas, collected over a 10-year period, was collocated and surveyed to assess the accuracy of satellite-observed sea surface temperatures (SST) and investigate the characteristics of satellite measured SST errors. This was done by subtracting insitu SST measurements from multi-channel SST (MCSST) measurements. 845 pieces of collocated data revealed that MCSST measurements had a root-mean-square error of about 0.89$^{\circ}C$ and a bias error of about 0.18$^{\circ}C$. The SST errors revealed a large latitudinal dependency with a range of $\pm3^{\circ}C$ around 40$^{\circ}N$, which was related to high spatial and temporal variability from smaller eddies, oceanic currents, and thermal fronts at higher latitudes. The MCSST measurements tended to be underestimated in winter and overestimated in summer when compared to in-situ measurements. This seasonal dependency was discovered from shipboard and moored buoy measurements, not satellite-tracked surface drifters, and revealed the existence of a strong vertical temperature gradient within a few meters of the upper ocean. This study emphasizes the need for an effort to consider and correct the significant skin-bulk SST difference which arises when calculating SST from satellite data.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.543-559
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• 2019

Data often include missing values due to various reasons. If the missing data mechanism is not MCAR, analysis based on fully observed cases may an estimation cause bias and decrease the precision of the estimate since partially observed cases are excluded. Especially when data include many variables, missing values cause more serious problems. Many imputation techniques are suggested to overcome this difficulty. However, imputation methods using parametric models may not fit well with real data which do not satisfy model assumptions. In this study, we review imputation methods using nonlinear models such as kernel, resampling, and spline methods which are robust on model assumptions. In addition, we suggest utilizing imputation classes to improve imputation accuracy or adding random errors to correctly estimate the variance of the estimates in nonlinear imputation models. Performances of imputation methods using nonlinear models are compared under various simulated data settings. Simulation results indicate that the performances of imputation methods are different as data settings change. However, imputation based on the kernel regression or the penalized spline performs better in most situations. Utilizing imputation classes or adding random errors improves the performance of imputation methods using nonlinear models.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.8
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• pp.10-21
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• 1999

This paper describes a 12bit CMOS current cell matrix D/A converter which shows a conversion rate of 65MHz and a power supply of 3.3V. Designed D/A converter utilizes current cell matrix structure with good monotonicity characteristic and fast settling time, and it is implemented by using the tree structure bias circuit, the symmetrical routing method with ground line and the cascode current switch to reduce the errors of the conventional D/A converter caused by a threshold voltage mismatch of current cells and a voltage drop of the ground line. The designed D/A converter was implemented with a $0.6{\mu}m$ CMOS n-well technology. The measured data shows a settling time of 20ns, a conversion rate of 50 MHz and a power dissipation of 35.6mW with a single power supply of 3.3V. The experimental SNR, DNL, and INL of the D/A converter is measured to be 55dB, ${\pm}0.5LSB$, and ${\pm}2LSB$, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.403-412
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• 2018

Recently, GNSS (Global Navigation Satellite System)-derived orthometric height determination has been studied to improve the time and cost-effectiveness of traditional leveling surveying. However, the accuracy of this new survey method was evaluated when unknown points are located lower than control points. In this study, the accuracy of GNSS-derived orthometric height was examined using TPs (Triangulation Points) to verify the stability of surveying in mountainous areas. The GNSS survey data were obtained from Mungyeong, Unbong/Hadong, Uljin, and Jangseong. Three unknown points were surrounded by more than three UCPs (Unified Control Points) or BMs (Benchmarks) following the guideline for applying GNSS-derived orthometric height determination. A newly developed national geoid model, KNGeoid17 (Korean National Geoid 2017), has been applied for determining the orthometric height. In comparison with the official orthometric heights of the TPs, the heights of the unknown points in Mungyeong and Unbong/Hadong differ by more than 20 cm. On the other hand, TPs in Uljin and Jangseong show 15-16 cm of local bias with respect to the official products. Since the precision of official orthometric heights of TPs is known to be about 10 cm, these errors exceed the limit of the precision. Therefore, the official products should be checked to offer more reliable results to surveyors. As an alternative method of verifying accuracy, three different GNSS post-processing software were applied, and the results from each software were compared. The results showed that the differences in the whole test areas did not exceed 5 cm. Therefore, it was concluded that the precision of the GNSS-derived orthometric height was less than 5 cm, even though the unknown points were higher than the control points.

• Journal of Preventive Medicine and Public Health
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• v.32 no.4
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• pp.513-525
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• 1999

Objectives : High-normal blood pressure' is a factor influencing decision to initiate targeted intensive intervention strategy in westernized populations. JNC-VI offered the vigorous lifestyle modification for persons with 'high-normal blood pressure', who could be early detected. As a hypertension seems to be the result of multiple genetic factors operating in concert with associated environmental factors, it will be necessary to identify the high-normal blood pressure as a risk factor of hypertension for applying primary prevention strategy in Korean people. Methods : Although cohort study design might be adequate to recruit incidence cases, to keep time sequence of events, and to prevent information bias, nested case-control study was chosen for avoiding measurement errors because hypertension is a benign disease. Source population was the 'Seoul Cohort' participants and follow-up was done by using Korea Medical Insurance Corporation's database on the utilization of health services from 1 Jan93 to 30Jun97. Incidence cases were ascertained through the chart review, telephone contacts, and direct blood pressure measurements. Controls included the pairing of 4 individuals to each case on the basis of age. Results : As 75% of 247 incident cases had high-normal blood pressure, the crude odds ratio for hypertension was 2.04 (95% CI 1.47-2.83). Another statistically significant risk factors of hypertension were body mass index, dietary fiber, alcohol consumption, weekly activity and history of quitting smoking. The multivariate odds ratio of high-normal blood pressure adjusted for all risk factors was 1.84 (95% CI 1.31-2.56). Among high-normal blood pressure group, body mass index, weekly ethanol amounts, weekly physical activity, and dietary fiber except history of quitting smoking were still risk factors of hypertension. Conclusion : 'High-normal blood pressure' is a risk factor for hypertension in Korean middle-aged men, which represents that the vigorous lifestyle modification for persons with 'high-normal blood pressure' is need.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• Survey Research
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• v.10 no.2
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• pp.1-21
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• 2009

The purpose of this study is to compare the estimates of housework time by gender using two representative methods of time use study: Time Diary and Stylized Survey Questionnaire. Our analysis is based on the data from the Lifetime Use Survey(2004), which used time-diary questions, and the Korean Labor & Income Panel Study(KLIPS 2004), which used stylized questions on housework hours. The results show that men over-report their housework time in the stylized time use questions. In contrast, women under-report their housework time, which is unusual in the previous studies on response errors and reporting gap. Subgroup analysis shows that widowed/divorced men tend to over-report their contribution to housework more than other groups whereas among women, groups burdened with employed work, caring and housework underestimate their housework time. This reporting gap is explained by gendered norm and perception of time pressure. The theory to explain under-reporting of the housework time has been undeveloped in the previous studies. Our study suggests that perceptions of time pressure be an important factor to explain women's reporting gap of housework estimates.

• Atmosphere
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• v.26 no.4
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• pp.599-615
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• 2016

This study investigates the accuracy of short-term ocean predictions during the development of ocean stratification for the Korea Meteorological Administration (KMA) Global Seasonal Forecast System version 5 (GloSea5) as well as the effect of atmosphere-ocean coupling on the predictions through a series of sensitive numerical experiments. Model performance is evaluated using the marine meteorological buoys at seas around the Korean peninsular (KP), Tropical Atmosphere Ocean project (TAO) buoys over the tropical Pacific ocean, and ARGO floats data over the western North Pacific for boreal winter (February) and spring (May). Sensitive experiments are conducted using an ocean-atmosphere coupled model (i.e., GloSea5) and an uncoupled ocean model (Nucleus for European Modelling of the Ocean, NEMO) and their results are compared. The verification results revealed an overall good performance for the SST predictions over the tropical Pacific ocean and near the Korean marginal seas, in which the Root Mean Square Errors (RMSE) were $0.31{\sim}0.45^{\circ}C$ and $0.74{\sim}1.11^{\circ}C$ respectively, except oceanic front regions with large spatial and temporal SST variations (the maximum error reached up to $3^{\circ}C$). The sensitive numerical experiments showed that GloSea5 outperformed NEMO over the tropical Pacific in terms of bias and RMSE analysis, while NEMO outperformed GloSea5 near the KP regions. These results suggest that the atmosphere-ocean coupling substantially influences the short-term ocean forecast over the tropical Pacific, while other factors such as atmospheric forcing and the accuracy of simulated local current are more important than the coupling effect for the KP regions being far from tropics during the development of ocean stratification.

• Environmental Engineering Research
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• v.21 no.4
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• pp.333-340
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• 2016

An Artificial Neural Network including a Radial Basis Function (RBF) and a Time Delay Neural Network (TDNN) was used to predict total dissolved solid (TDS) in the river Zayanderud. Water quality parameters in the river for ten years, 2001-2010, were prepared from data monitored by the Isfahan Regional Water Authority. A factor analysis was applied to select the inputs of water quality parameters, which obtained total hardness, bicarbonate, chloride and calcium. Input data to the neural networks were pH, $Na^+$, $Mg^{2+}$, Carbonate ($CO{_3}^{-2}$), $HCO{_3}^{-1}$, $Cl^-$, $Ca^{2+}$ and Total hardness. For learning process 5-fold cross validation were applied. In the best situation, the TDNN contained 2 hidden layers of 15 neurons in each of the layers and the RBF had one hidden layer with 100 neurons. The Mean Squared Error and the Mean Bias Error for the TDNN during the training process were 0.0006 and 0.0603 and for the RBF neural network the mentioned errors were 0.0001 and 0.0006, respectively. In the RBF, the coefficient of determination ($R^2$) and the index of agreement (IA) between the observed data and predicted data were 0.997 and 0.999, respectively. In the TDNN, the $R^2$ and the IA between the actual and predicted data were 0.957 and 0.985, respectively. The results of sensitivity illustrated that $Ca^{2+}$ and $SO{_4}^{2-}$ parameters had the highest effect on the TDS prediction.