• Journal of Korea Water Resources Association
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• v.55 no.3
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• pp.177-189
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• 2022

The purpose of this study is to apply the d4PDF (Data for Policy Decision Making for Future Change) constructed from a large-scale ensemble climate simulation to estimate the probable rainfall with low frequency and high intensity. In addition, this study analyzes the uncertainty caused by the application of the frequency analysis by comparing the probable rainfall estimated using the d4PDF with that estimated using the observed data and frequency analysis at Geunsam, Imsil, Jeonju, and Jangsu stations. The d4PDF data consists of a total of 50 ensembles, and one ensemble provides climate and weather data for 60 years such as rainfall and temperature. Thus, it was possible to collect 3,000 annual maximum daily rainfall for each station. By using these characteristics, this study does not apply the frequency analysis for estimating the probability rainfall, and we estimated the probability rainfall with a return period of 10 to 1000 years by distributing 3,000 rainfall by the magnitude based on a non-parametric approach. Then, the estimated probability rainfall using d4PDF was compared with those estimated using the Gumbel or GEV distribution and the observed rainfall, and the deviation between two probability rainfall was estimated. As a result, this deviation increased as the difference between the return period and the observation period increased. Meanwhile, the d4PDF reasonably suggested the probability rainfall with a low frequency and high intensity by minimizing the uncertainty occurred by applying the frequency analysis and the observed data with the short data period.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.315-324
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• 2022

The experimental data obtained in a wave flume were analyzed using machine learning techniques to establish a model that predicts the input wave height of the wavemaker based on the waves that have experienced wave shoaling and to verify the performance of the established model. For this purpose, artificial neural network (NN), the most representative machine learning technique, and Gaussian process regression (GPR), one of the non-parametric regression analysis methods, were applied respectively. Then, the predictive performance of the two models was compared. The analysis was performed independently for the case of using all the data at once and for the case by classifying the data with a criterion related to the occurrence of wave breaking. When the data were not classified, the error between the input wave height at the wavemaker and the measured value was relatively large for both the NN and GPR models. On the other hand, if the data were divided into non-breaking and breaking conditions, the accuracy of predicting the input wave height was greatly improved. Among the two models, the overall performance of the GPR model was better than that of the NN model.

• Journal of Practical Agriculture & Fisheries Research
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• v.19 no.1
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• pp.119-128
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• 2017

The field trial was performed to evaluate the rice growth and yield in different direct seeding methods. The required time for seed emergence was for 8~ 9days in the tested direct seeding methods and there was high in seedling establishment according to wet hill-seeding with iron-coated seeds> wet hill-seeding with soil coverage>water seeding with iron-coated seeds and water seeding with pregerminated seeds as the conventional treatment. The rice plant height was taller in wet hill-seeding methods than that of water seeding with broadcasting method but there was not significant difference in terms of statistical analysis at 75day after seeding except the water seeding with pregerminated seeds. The growth of tiller number in the rice plant was highest in water seeding with iron-coated seeds. The milled rice yield was highest in water seeding with iron-coated seed being with 6.4t/ha and percentage of head rice was the highest in wet hill-seeding and water seeding with iron-coated seeds.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.515-522
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• 2023

The aim of this study was to quantitatively evaluate a new stem volume table for estimating the growth, carbon storage, and greenhouse gas (GHG) absorption in Cryptomeria japonica and Chamaecyparis obtusa stands and to provide suggestions for improving the domestic GHG inventory. Carbon storage and GHG absorption were estimated using growing stock data obtained from invariable sub-sample plots between the 6^th and 7^th national forest inventories. We assessed changes in growing stock using the parameters employed by Kozak (1988) and Versions 1 and 2 of the stem volume table. Version 2 has new stem tables for 16 species, including Cryptomeria japonica, which were unavailable in Version 1. Version 2 also includes new data for trees with diameters at breast height equal to or greater than 30 cm. We found greater growing stock values using Version 2 than Version 1 for both stands, and the differences were statistically significant (p<0.001). Applying the new stem volume table increased GHG absorption by 22% for the Cryptomeria japonica stand and 13% for the Chamaecyparis obtusa stand. The growing stock estimation method used in this study should therefore be applied to re-estimate GHG absorptions in the forestry sector to produce accurate statistics for the IPCC guidelines.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.2
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• pp.37-45
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• 2022

A simplified model using the lifetime distribution has been presented to estimate the Mean Residual Life (MRL) of rubble-mound breakwaters, which is not like a stochastic process model based on time-dependent history data to the cumulative damage progress of rubble-mound breakwaters. The parameters involved in the lifetime distribution can be easily estimated by using the upper and lower limits of lifetime and their likelihood that made a judgement by several experts taking account of the initial design lifetime, the past sequences of loads, and others. The simplified model presented in this paper has been applied to the rubble-mound breakwater with TTP armor layer. Wiener Process (WP)-based stochastic model also has been applied together with Monte-Carlo Simulation (MCS) technique to the breakwater of the same condition having time-dependent cumulative damage to TTP armor layer. From the comparison of lifetime distribution obtained from each models including Mean Time To Failure (MTTF), it has found that the lifetime distributions of rubble-mound breakwater can be very satisfactorily fitted by log-normal distribution for all types of cumulative damage progresses, such as exponential, linear, and logarithmic deterioration which are feasible in the real situations. Finally, the MRL of rubble-mound breakwaters estimated by the simplified model presented in this paper have been compared with those by WP stochastic process. It can be shown that results of the presented simplified model have been identical with those of WP stochastic process until any ages in the range of MTT F regardless of the deterioration types. However, a little of differences have been seen at the ages in the neighborhood of MTTF, specially, for the linear and logarithmic deterioration of cumulative damages. For the accurate estimation of MRL of harbor structures, it may be desirable that the stochastic processes should be used to consider properly time-dependent uncertainties of damage deterioration. Nevertheless, the simplified model presented in this paper can be useful in the building of the MRL-based preventive maintenance planning for several kinds of harbor structures, because of which is not needed time-dependent history data about the damage deterioration of structures as mentioned above.

• Journal of Radiation Protection and Research
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• v.33 no.4
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• pp.127-134
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• 2008

Potential economic impact of a hypothetical severe accident at a nuclear power plant(Uljin units 3/4) was estimated by applying the Delphi method, which is based on the expert judgements and opinions, in the process of quantifying uncertain factors. For the purpose of this study, it is assumed that the radioactive plume directs the inland direction. Since the economic risk can be divided into direct costs and indirect effects and more uncertainties are involved in the latter, the direct costs were estimated first and the indirect effects were then estimated by applying a weighting factor to the direct cost. The Delphi method however subjects to risk of distortion or discrimination of variables because of the human behavior pattern. A mathematical approach based on the Bayesian inferences was employed for data processing to improve the Delphi results. For this task, a model for data processing was developed. One-dimensional Monte Carlo Analysis was applied to get a distribution of values of the weighting factor. The mean and median values of the weighting factor for the indirect effects appeared to be 2.59 and 2.08, respectively. These values are higher than the value suggested by OECD/NEA, 1.25. Some factors such as small territory and public attitude sensitive to radiation could affect the judgement of panel. Then the parameters of the model for estimating the direct costs were classified as U- and V-types, and two-dimensional Monte Carlo analysis was applied to quantify the overall economic risk. The resulting median of the overall economic risk was about 3.9% of the gross domestic products(GDP) of Korea in 2006. When the cost of electricity loss, the highest direct cost, was not taken into account, the overall economic risk was reduced to 2.2% of GDP. This assessment can be used as a reference for justifying the radiological emergency planning and preparedness.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.75-85
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• 2017

A method to estimate hourly temperature profiles on calm and clear nights was developed based on temporal changes of inversion height and strength. A meteorological temperature profiler (Model MTP5H, Kipp and Zonen) was installed on the rooftop of the Highland Agriculture Research Institute, located in Daegwallyeong-myeon, Pyeongchang-gun, Gangwon-do. The hourly vertical distribution of air temperature was measured up to 600 m at intervals of 50 m from May 2007 to March 2008. Temperature and relative humidity data loggers (HOBO U23 Pro v2, Onset Computer Corporation, USA) were installed in the Jungdae-ri Valley, located between Gurye-gun, Jeollanam-do and Gwangyang-si, Jeollanam-do. These loggers were used to archive measurements of weather data 1.5 m above the surface from October 3, 2014, to November 23, 2015. The inversion strength was determined using the difference between the temperature at the inversion height, which is the highest temperature in the profile, and the temperature at 100 m from the surface. Empirical equations for the changes of inversion height and strength were derived to express the development of temperature inversion on calm and clear nights. To estimate air temperature near the ground on a slope exposed to crops, the equation's parameters were modified using temperature distribution of the mountain slope obtained from the data loggers. Estimated hourly temperatures using the method were compared with observed temperatures at 19 weather sites located within three watersheds in the southern Jiri-mountain in 2015. The mean error (ME) and root mean square error (RMSE) of the hourly temperatures were $-0.69^{\circ}C$ and $1.61^{\circ}C$, respectively. Hourly temperatures were often underestimated from 2000 to 0100 LST the next day. When temperatures were estimated at 0600 LST using the existing model, ME and RMSE were $-0.86^{\circ}C$ and $1.72^{\circ}C$, respectively. The method proposed in this study resulted in a smaller error, e.g., ME of $-0.12^{\circ}C$ and RMSE of $1.34^{\circ}C$. The method could be improved further taking into account various weather conditions, which could reduce the estimation error.

• Childhood Kidney Diseases
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• v.5 no.2
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• pp.164-175
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• 2001

Purpose : Alport syndrome is a hereditary nephrotic disease characterized by progressive nephrotic symptom, sensorineural hearing loss, ophthalmic abnormality, typical microscopic findings, and familial occurrence. In this study, we tried to find the risk factors related with its prognosis by taking a close observation on clinical symptoms of children with Alport syndrome reviewing retrospectively. Materials & methods : We chose children diagnosed as Alport syndrome in renal biopsy during 20 years(from 1980, Jan. until 1999, Dec.) who could receive follow up studies in tile department of pediatrics. They were divided into two groups by comparing renal function at the time of diagnosis and at current status. We compared several clinical aspects in them, and applied nonparametric test for statistical analysis. Results : The sex ratio(male:female) of 24 children was 3:1. The most common clinical symptom presented at their first visit was gross hematuria. Among those 24 children, 11 cases($46\%$) of progressing into chronic renal failure(Group II) were observed. Hypertension, proteinuria and edema were seen much frequently in group II. The level of serum protein, albumin, and creatinine clearance were decreased while BUN, creatinine were relatively increased. All the results were statistically significant. Conclusion Clinically significant risk factors related to prognosis in Alport syndrome were the presence of hypertension, edema, and proteinuria at the time of diagnosis. Also, the level of serum protein, albumin, BUN, creatinine, and glomerular filtration rate were proved to be important factors in predicting prognosis. We believe that studies on these possible risk factors would be of great help in treating and predicting prognosis of children suffering with Alport syndrome. (J Korean Soc Pediatr Nephrol 2001;5 : 164-75)

• Journal of dental hygiene science
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• v.14 no.1
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• pp.67-73
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• 2014

This study analyzed 548 pieces of these, which were reported in the Journal of Dental Hygiene Science of having been published from 2001 to Vol. 12, No. 6 in 2012. In conclusion, as for analysis of research design, first, it was the largest in cross sectional research. Second, the research subjects of survey theses were higher in order of dental hygienist and dental hygiene student. Third, number of thesis authors was the largest in order of two persons and three persons. Fourth, statistical method was in order of descriptive statistics, t-test, and ANOVA. Research theme was in order of dental health behavioral science and clinical dental hygiene. Fifth, as for research-expense benefit, only 17.7% was supported research funds. As a result of this study, there should be a research on thesis of diverse designs in the future. There is a need of being performed actively a research on alienated classer or special subjects as well as a research on activity related to dental hygiene.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.311-320
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• 2007

This paper presents vision-based 3D facial expression animation technique and system which provide the robust 3D head pose estimation and real-time facial expression control. Many researches of 3D face animation have been done for the facial expression control itself rather than focusing on 3D head motion tracking. However, the head motion tracking is one of critical issues to be solved for developing realistic facial animation. In this research, we developed an integrated animation system that includes 3D head motion tracking and facial expression control at the same time. The proposed system consists of three major phases: face detection, 3D head motion tracking, and facial expression control. For face detection, with the non-parametric HT skin color model and template matching, we can detect the facial region efficiently from video frame. For 3D head motion tracking, we exploit the cylindrical head model that is projected to the initial head motion template. Given an initial reference template of the face image and the corresponding head motion, the cylindrical head model is created and the foil head motion is traced based on the optical flow method. For the facial expression cloning we utilize the feature-based method, The major facial feature points are detected by the geometry of information of the face with template matching and traced by optical flow. Since the locations of varying feature points are composed of head motion and facial expression information, the animation parameters which describe the variation of the facial features are acquired from geometrically transformed frontal head pose image. Finally, the facial expression cloning is done by two fitting process. The control points of the 3D model are varied applying the animation parameters to the face model, and the non-feature points around the control points are changed by use of Radial Basis Function(RBF). From the experiment, we can prove that the developed vision-based animation system can create realistic facial animation with robust head pose estimation and facial variation from input video image.