• The KSFM Journal of Fluid Machinery
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• v.18 no.6
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• pp.63-70
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• 2015

This paper proposes a novel airfoil named "KA2" for the blade of the wind turbine systems. Dynamic loads characteristics are analyzed and compared using aerodynamic data of ten airfoils including the proposed airfoil. The blade is divided into the sixteen elements in the longitudinal direction of the blade for applying the Blade Element Method Theory (BEMT) method, and in each element, torque, thrust, and pitching moment are calculated using turbulent time varying wind speed and aerodynamic data of each wing. Additionally, each force and torque is accumulated in the whole region of the blade for the estimation of representative values. The magnitude of such forces is comparatively analyzed for different airfoils. The angle of attack is constant below the rated wind speed due to the fact that the tip speed ratio is kept at the constant value, and it increases in the region of over rated wind speed as the tip speed ratio decreasing with constant rated rpm and increasing wind speed. Such increase in the angle of attack causes the changes of the force acting on the airfoil with different characteristics of lift and drag in the stall region of each different airfoil. Even though the mean wind speed is in the rated speed in a given time, because of the turbulence, it has either the over rated or under rated speed most of the time. Furthermore, the dynamic properties of each force are analyzed in this rated wind speed in order to objectively understand the dynamic properties of the blades which are designed based on the different airfoils. These dynamic properties are also compared by the standard deviation of time varying characteristics. Moreover, the output characteristics of the wind turbine are investigated with different airfoils and wind speeds. Based on these investigations, it was revealed that the proposed airfoil (KA2) is well applicable to the blade with passive pitch control system.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.479-485
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• 2022

At the Korea Institute of Radiological and Medical Sciences, physical human phantoms were developed to evaluate various radiation protection quantities, based on the mesh-type reference computational phantoms of the International Commission on Radiological Protection. The physical human phantoms were fabricated such that a radiophotoluminescent glass dosimeter (RPLGD) with a Tin filter, namely GD-352M, could be inserted into them. A Tin filter is used to eliminate the overestimated signals in low-energy photons below 100 keV. The measurement uncertainty of the RPLGD reader system based on GD-352M should be analyzed for obtaining reliable protection quantities before using it for practical applications. Generally, the measurement uncertainty of RPLGD systems without Tin filters is analyzed for quality assurance of radiotherapy units using a high-energy photon beam. However, in this study, the measurement uncertainty of GD-352M was analyzed for evaluating the protection quantities. The measurement uncertainty factors in the RPLGD include the reference irradiation, regression curve, reproducibility, uniformity, energy dependence, and angular dependence, as described by the International Organization for Standardization (ISO). These factors were calculated using the Guide to the Expression of Uncertainty in Measurement method, applying ISO/ASTM standards 51261(2013), 51707(2015), and SS-ISO 22127(2019). The measurement uncertainties of the RPLGD reader system with a coverage factor of k = 2 were calculated to be 9.26% from 0.005 to 1 Gy and 8.16% from 1 to 10 Gy. A blind test was conducted to validate the RPLGD reader system, which demonstrated that the readout doses included blind doses of 0.1, 1, 2, and 5 Gy. Overall, the E_n values were considered satisfactory.

• Korean Journal of Community Nutrition
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• v.27 no.3
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• pp.245-253
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• 2022

Objectives: This study was conducted to find out if the dietary iron intake of Koreans estimated by 2 different methods (iron content sources) using the food intake data from the Korea National Health and Nutrition Examination Survey (KNHANES) are comparable. One method was based on the KNHANES's Food & Nutrient Database (FND) derived mainly from the Korean Food Composition Table and the other used the iron content (IC) of food samples processed in the Korean Total Diet Study (KTDS). Methods: Dietary intake data from the 2013-2016 KNHANES was used to select representative foods (RFs) in KTDS for iron analysis. Selection of the RFs and cooking methods for each RF (RF × cooking method pair) was performed according to the 'Guidebook for Korean Total Diet Studies' and resulted in a total of 132 RFs and 224 'RF × cooking method' pairs. RFs were collected in 9 metropolitan cities nationwide once or twice (for those with seasonality) in 2018 and made into 6 composites each, based on the origin and season prior to cooking. Then, the RF composites prepared to a 'table ready' state for KTDS were analyzed by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Dietary iron intake of the Korean population was estimated using only RFs' intake data based on the 2 sources of iron content, namely FND-KNHANES and IC-KTDS. Results: RFs in KTDS covered 92.0% of total food intake of Koreans in the 2016-2018 KNHANES. Mean iron intake of Koreans was 7.77 mg/person/day by IC-KTDS vs 9.73 mg/person/day by FND-KNHANES. The major food groups contributing to iron intake were meats (21.7%), vegetables (20.5%), and grains & cereals (13.4%) as per IC-KTDS. On the other hand, the latter source (FND-KNHANES) resulted in a very different profile: grains & cereals (31.1%), vegetables (16.8%), and meats (15.3%). While the top iron source was beef, accounting for 8.6% in the former, it was polished rice (19.2%) in the latter. There was a 10-fold difference in the iron content of polished rice between 2 sources that iron intakes excluding the contribution by polished rice resulted in very similar values: 7.58 mg/person/day by IC-KTDS and 7.86 mg/person/day by FND-KNHANES. Conclusions: This study revealed that the dietary iron intake estimated by 2 different methods were quite comparable, excluding one RF, namely polished rice. KTDS was thus proven to be a useful tool in estimating a 'closer-to-real' dietary intake of nutrients for Koreans and further research on various nutrients is warranted.

• Journal of the Korean GEO-environmental Society
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• v.15 no.4
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• pp.29-36
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• 2014

The purpose of this study investigates the delivery characteristics according to the load of pollutants by calculating the delivery rate of targeted areas on pollutants in Sapkyo reservoir. The main rivers of Sapkyo reservoir are Namwoncheon, Dogocheon, Sapkyocheon, Muhancheon and Gokgyocheon. The delivery rate and their characteristics of five major rivers during rainfall season are investigated. As th result, biochemical oxygen demand (BOD), total nitrogen (T-N) and total phosphorous (T-P) of total delivery rate are calculated by 0.40, 0.34 and 0.08, respectively. The delivery rate of T-P compares to other water quality is investigated relatively low. Looked at the overall characteristics of the watershed, the delivery rate of T-N and T-P is little change in the rate of the year, too. The delivery rate of T-N is calculated from 0.2 to 0.3 in the dry season, and from 0.31 to 0.39 in a flood, respectively. The delivery rate of T-P is calculated to more than 0.3 in the dry season, and 0.11 in a flood. It is similar values which the average annual delivery rate of T-P is 0.08. Therefore, the measured delivery rate of Sapkyo reservoir can be applicable such as a delivery rate of similar features of the terrain and land use.

• Journal of Korean Society on Water Environment
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• v.35 no.6
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• pp.589-597
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• 2019

The purpose of this study was improve accuracy the IOPs inversion model(IOPs-IM) developed in 2016 for phycocyanin(PC) concentration estimation in the Nakdong River. Additionally, two optimum models were developed and evaluated with 2017 measurement field spectral data for the Geum River and the Yeongsan River. The used measurement data for IOPs-IM analyzation was randomly classified as training and verification materials at the ratio of 2:1 in all data sets. Using the training data set from 2015-2017, accuracy results of the IOPs-IM generally improved for the Nakdong River. The RMSE(Root Mean Square Error) decreased by 14 % compared to 2016. For the GeumRiver, the results of the IOPs-IM were suitable, except for some point results in 2016. Results of the IOPs-IM in the Yeongsan River followed the overall 1:1 line and MAE(Mean Absolute Error) was lower than other rivers. But the RMSE and MAE values were higher. As a result of applying the validation data to the IOPs-IM, the accuracy of the Nakdong River was reduced to RMSE 17.7 % and MRE 16.4 %, respectively compared with 2016. However, the MRE(Mean Relative Error) was estimated to be higher by 400 % in the Geum River, and the RMSE was more than 100 mg/㎥ of the Yeongsan River. Therefore, it is necessary to get the continuously data with various sections of each river for obtain objective and reliable results and the models should be improved.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Journal of Soil and Groundwater Environment
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• v.14 no.5
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• pp.29-40
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• 2009

In general, understanding groundwater flow in fractured bedrock is critical during tunnel and underground cavern construction. In that case, borehole data may be useful to examine groundwater flow properties of the fractured bedrock from pre-excavation until completion stages, yet sufficient borehole data is not often available to acquire. This study evaluated groundwater discharge rate into Jikri tunnel in Gyeonggi province using hydraulic parameters, groundwater level data in the later stage of tunneling, national groundwater monitoring network data, and electrical resistivity survey data. Groundwater flow rate into the tunnel by means of analytical method was estimated $7.12-74.4\;m^3/day/m$ while the groundwater flow rate was determined as $64.8\;m^3/day/m$ by means of numerical modeling. The estimated values provided by the numerical modeling may be more logical than those of the analytical method because the numerical modeling could take into account spatial variation of hydraulic parameters that was not possible by using the analytical method. Transient modeling for a period of one year from the tunnel completion resulted in the recovery of pre-excavation groundwater level.

• Knowledge Management Research
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• v.22 no.2
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• pp.247-268
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• 2021

Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.101-112
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• 2005

As we perceive the world as 3-dimensional through our two eyes, we can extract 3-dimensional information from stereo images obtained from two or more cameras. Since stereo images have a large amount of data, with recent advances in digital video coding technology, efficient compression algorithms have been developed for stereo images. In order to compress stereo images and to obtain 3-D information such as depth, we find disparity vectors by using disparity estimation algorithm generally utilizing pixel differences between stereo pairs. However, it is not unusual to have stereo images having different intensity values for several reasons, such as incorrect control of the iris of each camera, disagreement of the foci of two cameras, orientation, position, and different characteristics of CCD (charge-coupled device) cameras, and so on. The intensity differences of stereo pairs often cause undesirable problems such as incorrect disparity vectors and consequent low coding efficiency. By compensating intensity differences between left and right images, we can obtain higher coding efficiency and hopefully reduce the perceptual burden of brain to combine different information incoming from two eyes. We propose several methods of intensity compensation such as local intensity compensation, global intensity compensation, and hierarchical intensity compensation as very simple and efficient preprocessing tool. Experimental results show that the proposed algerian provides significant improvement in coding efficiency.