• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.119-133
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• 2022

One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.198-210
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• 2022

The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.374-381
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• 2023

The travel time of flash floods along mountain streams is mainly governed by reach-average velocity, rather than by the point velocity of the locations of interest. Reach-average velocity is influenced by various factors such as stream geometry, streambed materials, and the hydraulic roughness of streams. In this study, the reach-average velocity in mountain streams was measured for storm periods using rhodamine dye tracing. The point cloud data obtained from a LiDAR survey was used to extract the average hydraulic roughness height, such as R_a, R_max, and R_z. The size distribution of the streambed materials (D₅₀, D₈₄) was also considered in the estimation of the roughness height. The field experiments revealed that the reach-average velocities had a significant relationship with flow discharges (v = 0.5499Q^0.6165 ), with an R² value of 0.77. The root mean square error in the roughness height of the R_a-based estimation (0.45) was lower than those of the other estimations (0.47-1.04). Among the parameters for roughness height estimation, the R_a -based roughness height was the most reliable and suitable for developing the reach-average velocity equation for estimating the travel time of flood waves in mountain streams.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.83-91
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• 2008

Previous settlement prediction methods based on settlement monitoring were developed under instantaneous loading condition and have restriction to be applied to soft ground under ramp loading condition. In this study, settlement prediction method under ramp loading was developed. New settlement prediction method under ramp loading considered influence factors of consolidation settlement such as thickness of clayed layer, quantity of surcharge load and preconsolidation pressure, etc. Geometrical correction method based on hyperbolic method (1991) and correction method based on probability theory were applied to increase accuracy of settlement prediction using field monitoring data after ramp loading. Large consolidation tests for ideally controlled one dimensional consolidation under ramp loading condition were performed and the settlement behavior was predicted based on the monitoring data. New prediction method yielded good result of entire settlement behavior by using data during an early stage of ramp load. Additionally, new prediction method offered better settlement prediction which had final settlement prediction in close proximity and low RMSE(Root Mean Square Error) than previous method such as hyperbolic method did.

• Journal of the Korean Geotechnical Society
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• v.24 no.9
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• pp.41-48
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• 2008

The aim of this study is to present a graphical method in order to evaluate stages in shrinkage cracking. Firstly, the distribution of crack openings is established by sorting the openings of individual cracks in the soil cracking system. Secondly, it is normalized in a range of 0 to 1 to obtain the normalized crack opening distribution. Thirdly, three S-shape curve models introduced by Brooks and Corey(1964), Fredlund and Xing(1994) and van Genuchten(1980) are chosen to fit the normalized crack opening distribution using a curve fitting method. The accuracy of fitting which is described through fitting parameters by the van Genuchten equation is much higher than that by the Brooks and Corey equation and slightly higher than that by the Fredlund and Xing equation; thus the van Genuchten model is used. Finally, the stages of shrinkage cracking are graphically evaluated by drawing three separate straight lines corresponding to three linear parts of the fitted normalized crack opening distribution. The proposed method is tested with different sample thicknesses. The measured data are fitted by the selected model with the fairly high regression coefficient and small root mean square error. The results show graphically that shrinkage cracking comprises three stages; namely, primary, secondary and residual stages. Subsequently, the ranges of evaluated crack opening for each of these stages are presented.

• Journal of agriculture & life science
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• v.50 no.1
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• pp.95-104
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• 2016

The objective of this paper is to develop volume equation of street tree and its carbon stock for urban forest in Seoul. To develop the volume equation by major species in Seoul, data for street trees were obtained from four-species (e.g. Gingko biloba, Platanus occidentalis, Zelkova serrata, and Metasequoia glyptostroboides), which accounted for 79% all street trees in Seoul. This study used a variable based on diameter on breast height and four equation for calculating volume. The coefficient of determination, bias, and root mean square error were used to evaluate the precision of four equations. From these methods, the most suitable equations for Platanus occidentalis was aDb, the other was aD+bD2; coefficient of determination upper on 0.873. From the volume equation developed in this research, the estimated carbon stock were derived as about 33,760tC for four-species of urban forest in Seoul. The results of this paper offered volume equation and carbon stock that present growth information for street trees in urban forestry and these can be made available for evaluating the management for carbon in settlement.

• Journal of Korean Academy of Nursing
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• v.53 no.3
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• pp.295-308
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• 2023

Purpose: This study evaluated the validity and reliability of Shively and colleagues' self-efficacy for HIV disease management skills (HIV-SE) among Korean participants. Methods: The original HIV-SE questionnaire, comprising 34 items, was translated into Korean using a translation and back-translation process. To enhance clarity and eliminate redundancy, the author and expert committee engaged in multiple discussions and integrated two items with similar meanings into a single item. Further, four HIV nurse experts tested content validity. Survey data were collected from 227 individuals diagnosed with HIV from five Korean hospitals. Construct validity was verified through confirmatory factor analysis. Criterion validity was evaluated using Pearson's correlation coefficients with the new general self-efficacy scale. Internal consistency reliability and test-retest were examined for reliability. Results: The Korean version of HIV-SE (K-HIV-SE) comprises 33 items across six domains: "managing depression/mood," "managing medications," "managing symptoms," "communicating with a healthcare provider," "getting support/help," and "managing fatigue." The fitness of the modified model was acceptable (minimum value of the discrepancy function/degree of freedom = 2.49, root mean square error of approximation = .08, goodness-of-fit index = .76, adjusted goodness-of-fit index = .71, Tucker-Lewis index = .84, and comparative fit index = .86). The internal consistency reliability (Cronbach's α = .91) and test-retest reliability (intraclass correlation coefficient = .73) were good. The criterion validity of the K-HIV-SE was .59 (p < .001). Conclusion: This study suggests that the K-HIV-SE is useful for efficiently assessing self-efficacy for HIV disease management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.459-469
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• 2010

This study is to develop a grid-based daily runoff model considering seasonal vegetation canopy condition. The model simulates the temporal and spatial variation of runoff components (surface, interflow, and baseflow), evapotranspiration (ET) and soil moisture contents of each grid element. The model is composed of three main modules of runoff, ET, and soil moisture. The total runoff was simulated by using soil water storage capacity of the day, and was allocated by introducing recession curves of each runoff component. The ET was calculated by Penman-Monteith method considering MODIS leaf area index (LAI). The daily soil moisture was routed by soil water balance equation. The model was evaluated for 930 $km^2$ Yongdam watershed. The model uses 1 km spatial data on landuse, soil, boundary, MODIS LAI. The daily weather data was built using IDW method (2000-2008). Model calibration was carried out to compare with the observed streamflow at the watershed outlet. The Nash-Sutcliffe model efficiency was 0.78~0.93. The watershed soil moisture was sensitive to precipitation and soil texture, consequently affected the streamflow, and the evapotranspiration responded to landuse type.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.15-17
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• 2022

In the aftermath of the avian influenza that occurred from the second half of 2020 to the beginning of 2021, 17.8 million laying hens were slaughtered. Although the government invested more than 100 billion won for egg imports as a measure to stabilize prices, the effort was not that easy. The sharp volatility of egg prices negatively affected both consumers and poultry farmers, so measures were needed to stabilize egg prices. To this end, the egg prices were successfully predicted in this study by using the analysis algorithm of a machine learning regression. For price prediction, a total of 8 independent variables, including monthly broiler chicken production statistics for 2012-2021 of the Korean Poultry Association and the slaughter performance of the national statistics portal (kosis), have been selected to be used. The Root Mean Square Error (RMSE), which indicates the difference between the predicted price and the actual price, is at the level of 103 (won), which can be interpreted as explaining the egg prices relatively well predicted. Accurate prediction of egg prices lead to flexible adjustment of egg production weeks for laying hens, which can help decision-making about stocking of laying hens. This result is expected to help secure egg price stability.