• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.1
• /
• pp.1-8
• /
• 2019

Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study, a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was also integrated to derive the soil hydraulic properties(${\alpha}$, n, ${\Theta}_r$, ${\Theta}_s$, $K_s$) as the input variables to SWAP based on the soil information(Sand, Silt and Clay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) and long-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites of RDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statistics of Root Mean Square Error(RMSE: 0.034~0.069) and Temporal Correlation Coefficient(TCC: 0.735~0.869) for validation. When we predicted the mid-/long-term soil moisture values using the TIGGE(0~15 days)/S2S(16~46 days) weather forecasts, the soil moisture estimates showed less variations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based on the increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluating agricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.

• Analytical Science and Technology
• /
• v.32 no.2
• /
• pp.56-64
• /
• 2019

Recently, a number of adulterated products, which are advertised as hair-growth enhancer have been emerged among those who suffer hair loss disease. For continuous control of illegal products, in this study, a rapid and sensitive method for simultaneous screening of 12 compounds that enhance hair-growth was established to protect public health by ultrahigh-performance liquid chromatography coupled to quadrupole-orbitrap mass spectrometry (UHPLC-Q-Orbitrap-MS). Fragmentation pathways of them were proposed based on $MS^2$ spectral data obtained using the established method. In this analysis, the LODs and LOQs ranged from 0.05 to 50 ng/mL and from 0.17 to 167 ng/mL, respectively. The square of the linear correlation coefficient ($R^2$) was determined as more than 0.995. The intra- and inter-assay accuracies were respective 88-112 % and 88-115 %. Their precision values were measured within 5 % (intra-day) and 10 % (inter-day). Mean recoveries of target compounds in adulterated products ranged from 84 to 115%. The relative standard deviation of stability was less than 12 % at $4^{\circ}C$ for 48 h. The method was employed to screen 14 dietary supplements advertised to be effective for the treatment of hair loss. Some of the products (~21 %) were proven to contain synthetic drugs that promote hair growth such as triaminodil, minoxidil, and finasteride.

• Journal of the Korea Convergence Society
• /
• v.10 no.5
• /
• pp.157-163
• /
• 2019

This study empirically investigates the double jeopardy phenomenon in a Korean and a New Zealand context. The double jeopardy is that companies with a small market share tend to suffer not only smaller sales volumes but also suffer a lower price than the market leader. The research reported here analyses price and market share data for 14 categories of household goods in Korea and a smaller number in New Zealand. Analysis shows that, in Korea, leading brands do enjoy a price premium as predicted, of around 15%, but that there is little or no evidence of double jeopardy occurring in New Zealand. Based on this study, evidence suggests that market share is a strong valid strategic objective in the East.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.106-106
• /
• 2015

The information of flow regimes continues to be norm in water resource and watershed management, in that stream flow regime is a crucial factor influencing water quality, geomorphology, and the community structure of stream biota. The objectives of this study were to estimate Korean stream flows from landscape variables, classify stream flow gages using hydraulic characteristics, and then apply these methods to ungaged biological monitoring sites for effective ecological assessment. Here I used a linear modeling approach (MLR, PCA, and PCR) to describe and predict seasonal flow statistics from landscape variables. MLR models were successfully built for a range of exceedance discharges and time frames (annual, January, May, July, and October), and these models explained a high degree of the observed variation with r squares ranging from 0.555 (Q95 in January) to 0.899 (Q05 in July). In validation testing, predicted and observed exceedance discharges were all significantly correlated (p<0.01) and for most models no significant difference was found between predicted and observed values (Paired samples T-test; p>0.05). I classified Korean stream flow regimes with respect to hydraulic and hydrologic regime into four categories: flashier and higher-powered (F-HP), flashier and lower-powered (F-LP), more stable and higher-powered (S-HP), and more stable and lower-powered (S-LP). These four categories of Korean streams were related to with the characteristics of environmental variables, such as catchment size, site slope, stream order, and land use patterns. I then applied the models at 684 ungaged biological sampling sites used in the National Aquatic Ecological Monitoring Program in order to classify them with respect to basic hydrologic characteristics and similarity to the government's array of hydrologic gauging stations. Flashier-lower powered sites appeared to be relatively over-represented and more stable-higher powered sites under-represented in the bioassessment data sets.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.12 no.1
• /
• pp.213-225
• /
• 2020

Floating Offshore Wind Turbines (FOWT) installed in the deep sea regions where stable and strong wind flows are abundant would have significantly improved energy production capacity. When designing FOWT, it is essential to understand the stability and motion performance of the floater. Water tank model tests are required to evaluate these aspects of performance. This paper describes a model test and numerical simulation for a 750-kW semi-submersible platform wind turbine model-II. In the previous model test, the 750-kW FOWT model-I suffered slamming phenomena from extreme wave conditions. Because of that, the platform freeboard of model-II was increased to mitigate the slamming load on the platform deck structure in extreme conditions. Also, the model-I pitch Response Amplitude Operators (RAO) of simulation had strong responses to the natural frequency region. Thus, the hub height of model-II was decreased to reduce the pitch resonance responses from the low-frequency response of the system. Like the model-I, 750-kW FOWT model-II was built with a 1/40 scale ratio. Furthermore, the experiments to evaluate the performance characteristics of the model-II wind turbine were executed at the same location and in the same environment conditions as were those of model-I. These tests included a free decay test, and tests of regular and irregular wave conditions. Both the experimental and simulation conditions considered the blade rotating effect due to the wind. The results of the model tests were compared with the numerical simulations of the FOWT using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code from the National Renewable Energy Laboratory (NREL).

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.4
• /
• pp.83-91
• /
• 2021

Health is an outset of psychological, social, financial, and physical state. Several macroeconomic factors are entangled with health and mortality. Infant mortality and life expectancy are two keyguard on demographic research context on last few decades. On the other hand, foreign inflows play an unprecedent role for raising economic circulation and providing more opportunities to build a better society. The study aims to investigate the relationship between foreign direct investment (FDI), economic growth, and Bangladesh's health. This study employs time-series data from 1980 to 2018. Results show, with Auto-regressive Distribute Lag (ARDL) model, that there is significant cointegration among variables. Foreign investment and economic output relate significantly and positively to health. On the contrary, education is quasi-linked with a different sign-on different model. For model validation, pitfalls of time-series multicollinearity, heteroscedasiticy, and autocorrelation are not present. Also, CUSUM and CUSUMSQ tests are validating the model as stable and fit for future prediction. Medical assessment and education need more attention from the government as well as the private sector. FDI can play a catalyst role for improving the health sector, raising opportunity in educating and creating a better lifestyle. In order to optimize foreign investment, the government should implement necessary reforms and policies.

• Journal of The Geomorphological Association of Korea
• /
• v.24 no.1
• /
• pp.77-91
• /
• 2017

Many debris landforms in the mountains of Korea have formed in the periglacial environment during the last glacial stage when the generation of sediments was active. Because these landforms are generally located on steep slopes and mostly covered by vegetation, however, it is difficult to observe and access them through field investigation. A scientific method is required to reduce the survey range before performing field investigation and to save time and cost. For this purpose, the use of remote sensing and GIS technologies is essential. This study has extracted the potential area of debris landform formation using a fuzzy set model as a mathematical data integration method. The first step was to obtain information about the location of debris landforms and their related factors. This information was verified through field observation and then used to build a database. In the second step, we conducted the fuzzy set modeling to generate a map, which classified the study area based on the possibility of debris formation. We then applied a cross-validation technique in order to evaluate the map. For a quantitative analysis, the calculated potential rate of debris formation was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). The prediction accuracy of the model was found to be 83.1%. We posit that the model is accurate and reliable enough to contribute to efficient field investigation and debris landform management.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.26-36
• /
• 2020

The use of existing macroscopic research of pedestrian behavior on the walking link as data is limited in determining an individual pedestrian's moving route and the level of service. In macroscopic studies, it is difficult to make quantitative indices, such as pedestrian flow rate, occupied space, density, and speed for determining the level of service on pedestrian roads. Therefore, the microscopic pedestrian route is required to establish appropriate pedestrian policies. In this study, the Yeok-Sam subway station network was examined using a micro-simulation VISSIM, which was then calibrated and validated statistically. The Pedestrian Road's Level of Service of Yeok-Sam subway station area was evaluated using the pedestrian speed as the evaluating index on the Korean highway capacity handbook.

• The Korean Journal of Applied Statistics
• /
• v.34 no.2
• /
• pp.153-166
• /
• 2021

A main goal of pharmacogenomics studies is to predict individual's drug responsiveness based on high dimensional genetic variables. Due to a large number of variables, feature selection is required in order to reduce the number of variables. The selected features are used to construct a predictive model using machine learning algorithms. In the present study, we applied several hybrid feature selection methods such as combinations of logistic regression, ReliefF, TurF, random forest, and LASSO to a next generation sequencing data set of 400 epilepsy patients. We then applied the selected features to machine learning methods including random forest, gradient boosting, and support vector machine as well as a stacking ensemble method. Our results showed that the stacking model with a hybrid feature selection of random forest and ReliefF performs better than with other combinations of approaches. Based on a 5-fold cross validation partition, the mean test accuracy value of the best model was 0.727 and the mean test AUC value of the best model was 0.761. It also appeared that the stacking models outperform than single machine learning predictive models when using the same selected features.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.2
• /
• pp.78-84
• /
• 2021

In addition to physical risks such as electrical, chemical, and mechanic ones in the workplace, psychosocial risks are also raising as an important issue in recent years in connection with human rights and work-life balance policies. The purpose of this study is to confirm the degree of effect of the psychosocial risk management plan at the workplace on workers through logistic regression analysis. Input data for logistic regression analysis is the results of a survey of 4,558 people conducted by the Institute for Occupational Safety and Health were used. There are 9 independent variables, including the change a workplace and confidential counseling, and the dependent variable is whether the worker feels the effect on the psychosocial risk management plan. As a result of this study, changes in work organization, dispute resolution procedures, provision of education program, notification of the impact of psychosocial risks on safety and health, and the persons in charge of solving psychosocial problems are shown effective in reducing worker's psychosocial risks. This study drives which of the management plans implemented to reduce the psychosocial risk of workers in the workplace are effective, so it can contribute to the development of psychosocial risk management plans in the future.