• Journal of the Korean Regional Science Association
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• v.37 no.3
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• pp.3-18
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• 2021

The fourth Industrial Revolution is transforming the industrial structure of the region, and it is necessary to develop new industries and technologies that reflect regional characteristics. The purpose of this study is to measure the knowledge relatedness and technological complexity in Busan, Ulsan, and Gyeongnam, and to identify technologies with potential for regional industrial differentiation strategies. Using patent data from 2015 to 2019, co-occurrence matrices were derived from 652 IPC codes, and the knowledge relatedness density and technology complexity index were calculated. Network analysis was performed using the knowledge relatedness density. As a result of analysis, it was found that mechanical engineering occupied a large proportion, followed by chemistry and electrical engineering. As a result of applying the risk-benefit framework to derive technologies with the potential to differentiate local industries, the technological capabilities of low-risk-high-benefit were different. Among mechanical engineering, technologies such as engine, machine operation, and transportation were included in Busan. In Ulsan, environmental technology in chemical and materials, and heat treatment technology in mechanical engineering were technologies with low-risk and high-benefit capabilities. Gyeongnam showed competence in mechanical engineering, chemistry, and electrical engineering in some areas such as Gimhae, Yangsan, and Changwon. The results of this study are meaningful in that they identified technologies with potential for selecting and deriving strategic industries for regional growth based on latent knowledge in the region.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.273-280
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• 2021

In the past, the government made a total of 357 hydrophilic districts into parks to create rest areas in the national river with the four major river projects. According to the results of the survey, 60 water-friendly districts with low utilization were lifted in January 2017, and 297 water-friendly districts are currently being managed. Local governments are in charge of the maintenance costs necessary to maintain these hydrophilic districts, which require considerable costs, so it is necessary to accurately grasp the characteristics and needs of local residents at the operation stage after designation. In this study, the characteristics of local residents in the hydrophilic district were analyzed by correlating social factors with river users, crawling social network data to analyze visit patterns, and derived related Keywords, and analyzed the characteristics of the hydrophilic district. The study target areas are Samrak and Daejeo Ecological Park, located downstream of the Nakdonggang River. Social factors analyzed real estate transaction price data, economic activity income, households, stress perception rate, and pet breeding status through public data provided by Statistics Korea, and analyzed user visit patterns and image keywords on weekends.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.7
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• pp.199-204
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• 2021

Digital substation refers to a substation that digitizes functions and communication methods of power facilities such as monitoring, measuring, control, protection, and operation based on IEC 61850, an international standard for the purpose of intelligent power grids. Based on the intelligent operating system, efficient monitoring and control of power facilities is possible, and automatic recovery function and remote control are possible in the event of an accident, enabling rapid power failure recovery. With the development of digital technology and the expansion of the introduction of eco-friendly renewable energy and electric vehicles, the spread of direct current distribution systems is expected to expand. MVDC is a system that utilizes direct current lines with voltage levels and transmission capacities between HVDCs applied to conventional transmission systems and LVDCs from consumers. Converting existing lines in substations, where most power equipment is alternating current centric, to direct current lines will reduce transmission losses and ensure greater current capacity. The process bus of a digital substation is a communication network consisting of communication equipment such as Ethernet switches that connect installed devices between bay level and process level. For MVDC linkage to existing digital substations, the process level was divided into two buses: AC and DC, and a system that can be comprehensively managed in conjunction with diagnostic IEDs as well as surveillance and control was proposed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.273-281
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• 2019

The energy consumed by buildings among the total national energy consumption is more than 10% of the total. For this reason, Korea has adopted the zero energy building policy since 2025, and research on the energy saving technology of buildings has been demanded. Analysis of buildings' energy consumption patterns shows that lighting, heating and cooling energy account for more than 60% of total energy consumption, which is directly related to solar power acquisition and window opening and closing operation. In this paper, we have developed a low - power IoT sensor module for window system to transfer acquired information to building energy management system. This module transmits the external environment and window opening / closing status information to the building energy management system in real time, and constructs the network to actively take energy saving measures. The power used in the module is designed as an independent power source using solar power among the harvest energy. The topology of the power supply is a Buck converter, which is charged at 4V to the lithium ion battery through MPPT control, and the efficiency is about 85.87%. Communication is configured to be able to transmit in real time by applying WiFi. In order to reduce the power consumption of the module, we analyzed the hardware and software aspects and implemented a low power IoT sensor module.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.859-865
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• 2018

A construction of infrastructures and base station on the moon could be undertaken by linking with the regions where construction materials and energy could be supplied on site. It is necessary to detect craters on the lunar surface and gather their topological information in advance, which forms permanent shaded regions (PSR) in which rich ice deposits might be available. In this study, an effective method for automatic detection of lunar craters on the moon surface is taken into consideration by employing a latest version of deep-learning algorithm. A training of a deep-learning algorithm is performed by involving the still images of 90000 taken from the LRO orbiter on operation by NASA and the label data involving position and size of partly craters shown in each image. the Faster RCNN algorithm, which is a latest version of deep-learning algorithms, is applied for a deep-learning training. The trained deep-learning code was used for automatic detection of craters which had not been trained. As results, it is shown that a lot of erroneous information for crater's positions and sizes labelled by NASA has been automatically revised and many other craters not labelled has been detected. Therefore, it could be possible to automatically produce regional maps of crater density and topological information on the moon which could be changed through time and should be highly valuable in engineering consideration for lunar construction.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.1
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• pp.17-29
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• 2019

This study developed prediction models of chlorine bulk decay coefficient by each condition of water quality, measuring chlorine bulk decay coefficients of the water and water quality by water purification processes. The second-reaction order of chlorine were selected as the optimal reaction order of research area because the decay of chlorine was best represented. Chlorine bulk decay coefficients of the water in conventional processes, advanced processes before rechlorination was respectively $5.9072(mg/L)^{-1}d^{-1}$ and $3.3974(mg/L)^{-1}d^{-1}$, and $1.2522(mg/L)^{-1}d^{-1}$ and $1.1998(mg/L)^{-1}d^{-1}$ after rechlorination. As a result, the reduction of organic material concentration during the retention time has greatly changed the chlorine bulk decay coefficient. All the coefficients of determination were higher than 0.8 in the developed models of the chlorine bulk decay coefficient, considering the drawn chlorine bulk decay coefficient and several parameters of water quality and statistically significant. Thus, it was judged that models that could express the actual values, properly were developed. In the meantime, the chlorine bulk decay coefficient was in proportion to the initial residual chlorine concentration and the concentration of rechlorination; however, it may greatly vary depending on rechlorination. Thus, it is judged that it is necessary to set a plan for the management of residual chlorine concentration after experimentally assessing this change, utilizing the methodology proposed in this study in the actual fields. The prediction models in this study would simulate the reduction of residual chlorine concentration according to the conditions of the operation of water purification plants and the introduction of rechlorination facilities, more reasonably considering water purification process and the time of chlorination. In addition, utilizing the prediction models, the reduction of residual chlorine concentration in the supply areas can be predicted, and it is judged that this can be utilized in setting plans for the management of residual chlorine concentration.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.14-25
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• 2018

The operation of high-speed rail (HSR) has an effect on the agglomeration economies, and the impact is shown as a relocation of individual firm and worker to where business activity can be maximized. The proximity to the HSR station could be considered as a core district to maximize the industrial benefit through the HSR network. From this perspective, this study considers the agglomeration effect of HSR within the HSR station-area and analyzed the agglomerated spatial pattern through hotspot analysis by service industry in the cases of Korea and Japan using GIS. This study analyzed the service industry within 1km distance from 8 HSR stations of Korea and 4 Kyushu Shinkansen stations of Japan. The results suggest that the hotspot patterns are observed in the service industry within 1km distance from the HSR station of Korea and Japan, except for two HSR stations of Gupo station and Kagoshima-Chuo station. Leisure, amusement, association, and other specific service industries could be affected by HSR passengers and knowledge-spillovers through HSR station. Therefore, the observed hotspot districts near the HSR station-area could explain an agglomeration pattern of the service industry through a closeness to the HSR station. Further, we could expect that the impact of HSR affects the service industry, and the impact could attract business activities of the service-area to maximize their benefit from HSR travelers. With the result, it is required to build up a supportive policy to maximize the HSR's impact on the service industry when considering the HSR station-area development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.435-447
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• 2019

In order to prevent unnecessary re-admission, it is necessary to intensively manage the groups with high probability of re-admission. For this, it is necessary to develop a re-admission prediction model. Two - year discharge summary data of one university hospital were collected from 2016 to 2017 to develop a predictive model of re-admission. In this case, the re-admitted patients were defined as those who were discharged more than once during the study period. We conducted descriptive statistics and crosstab analysis to identify the characteristics of rehospitalized patients. The re-admission prediction model was developed using logistic regression, neural network, and decision tree. AUC (Area Under Curve) was used for model evaluation. The logistic regression model was selected as the final re-admission predictive model because the AUC was the best at 0.81. The main variables affecting the selected rehospitalization in the logistic regression model were Residental regions, Age, CCS, Charlson Index Score, Discharge Dept., Via ER, LOS, Operation, Sex, Total payment, and Insurance. The model developed in this study was limited to generalization because it was two years data of one hospital. It is necessary to develop a model that can collect and generalize long-term data from various hospitals in the future. Furthermore, it is necessary to develop a model that can predict the re-admission that was not planned.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.633-642
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• 2021

Growing demand for electricity, when combined with the need to limit carbon emissions, drives a huge increase in renewable energy industry. In the electric power system, electricity supply always needs to be balanced with electricity demand and network losses to maintain safe, dependable, and stable system operation. There are three broad challenges when it comes to a power system with a high penetration of renewable energy: transient stability, small signal stability, and frequency stability. Transient stability analyze the system response to disturbances such as the loss of generation, line-switching operations, faults, and sudden load changes in the first several seconds following the disturbance. Small signal stability refers to the system's ability to maintain synchronization between generators and steady voltages when it is subjected to small perturbations such as incremental changes in system load. Frequency stability refers to the ability of a power system to maintain steady frequency following a severe system upset resulting in significant imbalance between generation and load. In this paper, we discusses these stability using system simulation by renewable energy deployment plan, and also analyses the influence of the renewable energy sources to the grid stability.

• Journal of Navigation and Port Research
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• v.44 no.6
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• pp.541-549
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• 2020

This study conducts differential analysis on the financial positions of Korean shipping companies before and after the bankruptcy of the H carrier, looking specifically at their financial ratios, profit and loss patterns, and other factors related to their financial operation. Firstly, it was discovered that major measures of financial health, such as average assets per carrier, were not affected by the bankruptcy of the H carrier. However, despite this, most carriers experienced large changes in profits and losses, with total sales and shipping revenues averaging 424.5 billion won and 381.7 billion won respectively before the bankruptcy, but falling by half to 252.1 billion won and 234.6 billion won after the bankruptcy. Additionally, charter revenues and expenses also dropped by more than half. EBIT/sales and pre-tax revenue margins were also heavily affected after the bankruptcy, with both figures averaging 8% and 3% respectively before the bankruptcy, but falling into the negative range at -2% and -8% post-bankruptcy, resulting in significant deterioration in operational profitability. The study concludes that there is an urgent need to establish a global sales network, improve cost structures, and consistently secure stable cargo in order to increase Korean carriers' profitability. Of all financial measures, liquidity and total asset efficiency were identified as the most severely-impacted by the H carrier bankruptcy, thereby requiring the most pressing policy addressing.