• Korean Journal of Remote Sensing
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• v.39 no.5_4
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• pp.1135-1144
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• 2023

Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.21-38
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• 2024

The current situation of ports and related industries is transitioning from quantitative growth in increased cargo volume and expansion of port facilities to qualitative growth in the role of ports through the creation of high value-added. Ports are now recognized as playing an important role in economic growth and development by generating high value-added, not just by increasing the amount of cargo and expanding port facilities. This study evaluated the importance of factors affecting the improvement of the Busan Port's marine equipment industry by using the Analytic Hierarchy Process(AHP) to derive the priority of improvement measures by factor and evaluate the importance of factors affecting the marine equipment industry. The factors that should be considered when selecting improvement measures for the marine equipment industry were selected as four factors: strengthening price competitiveness, increasing government and local government interest, strengthening promotion, and establishing a global network. The main sub-factors were composed of eight detailed evaluation factors by selecting two factors for each layer. The analysis was designed by dividing the factor hierarchy for selecting improvement measures for the marine equipment industry into three levels and creating survey questions for pairwise comparison. The priority of the analysis results using AHP showed that the factor with the highest priority was strengthening price competitiveness, followed by increasing government and local government interest, establishing a global network, and strengthening promotion. According to the analysis results for the second-level sub-factors, among the factors for strengthening price competitiveness, low distribution costs and storage costs were considered most important, followed by avoiding excessive competition among marine equipment companies. Among the factors for increasing government and local government interest, improving customs procedures and tariff refund procedures were considered most important, followed by strengthening incentives from the government and Busan City. Among the factors for establishing a global network, promoting large-scale marine equipment companies was considered most important, followed by actively participating in international marine equipment-related associations. Among the factors for strengthening promotion, active use of the Internet was considered most important, followed by holding domestic and international exhibitions. Based on this study, we hope to help activate Busan Port's market by enhancing its competitiveness through revitalizing its marine equipment industry, generating water traffic, and creating new value-added.

• Journal of the Korea Organic Resources Recycling Association
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• v.25 no.2
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• pp.41-48
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• 2017

A vertical multi-stage ammonia stripping reactor using E-PFR, which has been proved to be superior in anaerobic and aerobic treatment, was developed and a lab scale experiment was conducted. According to the change of stage number condition, the removal rate of the ammonia nitrogen in the reactor with 0-stage was about 52.5% after 8 hours (pH 10, temperature $35^{\circ}C$, and the air/liquid ratio $3min^{-1}$) However, in the reactor with 5-stage, the removal efficiency was about 62.6%. According to the change of pH condition, the removal rate of ammonia nitrogen was about 42.6% at pH 9 after 8 hours, and was about 74.4% at pH 11 (5-stage reactor, temperature $35^{\circ}C$, and the air/liquid ratio $3min^{-1}$). According to the change of temperature condition, the removal rate of the ammonia nitrogen was about 51% at $25^{\circ}C$ after 8 hours (5-stage reactor, pH 10, and the air/liquid ratio $3min^{-1}$), and was about 87.2% at $45^{\circ}C$. According to the change of air injection volume condition, the removal rate of the ammonia nitrogen was about 45.8% at $2min^{-1}$ after 8 hours (5-stage reactor, pH 10, and at $35^{\circ}C$). and was about 75% at $4min^{-1}$. Based on these results, we will follow up the applicability of the actual plant in the future through continuous operation evaluation.

• Journal of Life Science
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• v.23 no.1
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• pp.116-124
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• 2013

The aim was to examine resistance exercise-related genes after 8 weeks of resistance training. Thirty-two male Sprague-Dawley rats were divided into four groups: 4 weeks sedentary (4 wks CON, n=8), 8 weeks sedentary (8 wks CON, n=8), 4 weeks exercise training (4 wks REG, n=8), and 8 weeks exercise training (8 wks REG, n=8). The rats were trained to climb a 1-m vertical incline (85-degree), with weights secured to their tails. They climbed 10 times, 3 days per week, for 8 consecutive weeks. Skeletal muscle was taken from the flexor halucis longus after the exercise training. After separating the total RNA, large-scale gene expression was investigated by beadarray (Illumina RatRef-12 Expression BeadChip) analysis, and qPCR was used to inspect the beadarray data and to analyze the RNA quantitatively. The detection p-value for the genes was p<0.01, the M-value {M=$log_2$(condition)-$log_2$(reference)} was >1.0, and the DiffScore was >20. In total, the expression of 30 genes significantly increased 4 weeks after the exercise training, and the expression of six genes decreased. At 8 weeks, the expression of five genes significantly increased and that of 12 decreased. Several genes are potentially involved in resistance exercise and muscle hypertrophy, including 1) regulation of cell growth (IGFBP1, PLA2G2A, OKL38); 2) myogenesis (CSRP3); 3) tissue regeneration and muscle development (MUSTN1, MYBPH); 4) hypertrophy (CYR61, ATF3, NR4A3); and 5) glucose metabolism (G6PC, PCK1). These results may help to explain previously reported physiological changes of the skeletal muscle and suggest new avenues for further investigation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.167-175
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• 2019

To effectively deal with the fire in tunnel which is mostly the vehicle fire, it's more important to suppress the fire at early stage. In urban tunnel, however, accessibility to the scene of fire by the fire fighter is very limited due to severe traffic congestion which causes the difficulty with firefighting activity in timely manner and such a problem would be further worsened in underground road (double-deck tunnel) which has been increasingly extended and deepened. In preparation for the disaster in Korea, the range of life safety facilities for installation is defined based on category of the extension and fire protection referring to risk hazard index which is determined depending on tunnel length and conditions, and particularly to directly deal with the tunnel fire, fire extinguisher, indoor hydrant and sprinkler are designated as the mandatory facilities depending on category. But such fire extinguishing installations are found inappropriate functionally and technically and thus the measure to improve the system needs to be taken. Particularly in a double-deck tunnel which accommodates the traffic in both directions within a single tunnel of which section is divided by intermediate slab, the facility or the system which functions more rapidly and effectively is more than important. This study, thus, is intended to supplement the problems with existing tunnel life safety system (fire extinguishing) and develop the remote-controlled automatic fire extinguishing system which is optimized for a double-deck tunnel. Consequently, the system considering low floor height and extended length as well as indoor hydrant for a wide range of use have been developed together with the performance verification and the process for commercialization before applying to the tunnel is underway now.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.115-124
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• 2023

Currently, as the frequency of extreme weather events increases, the scale of damage increases when extreme weather events occur. This has been providing forecast information by investing a lot of time and resources to predict rainfall from the past. However, this information is difficult for non-experts to understand, and it does not include information on how much damage occurs when extreme weather events occur. Therefore, in this study, a risk matrix based on heavy rain damage rating was presented by using the impact forecasting standard through the creation of a risk matrix presented for the first time in the UK. First, through correlation analysis between rainfall data and damage data, variables necessary for risk matrix creation are selected, and PERCENTILE (25%, 75%, 90%, 95%) and JNBC (Jenks Natural Breaks Classification) techniques suggested in previous studies are used. Therefore, a rating standard according to rainfall and damage was calculated, and two rating standards were synthesized to present one standard. As a result of the analysis, in the case of the number of households affected by the disaster, PERCENTILE showed the highest distribution than JNBC in the Yeongsan River and Seomjin River basins where the most damage occurred, and similar results were shown in the Chungcheong-do area. Looking at the results of rainfall grading, JNBC's grade was higher than PERCENTILE's, and the highest grade was shown especially in Jeolla-do and Chungcheong-do. In addition, when comparing with the current status of heavy rain warnings in the affected area, it can be confirmed that JNBC is similar. In the risk matrix results, it was confirmed that JNBC replicated better than PERCENTILE in Sejong, Daejeon, Chungnam, Chungbuk, Gwangju, Jeonnam, and Jeonbuk regions, which suffered the most damage.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.236-256
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• 2011

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.