• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.581-589
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• 2021

With the recent increase in the introduction of micro-electric vehicles in Korea, interest in micro-electric vehicle user satisfaction is increasing to revitalize related markets. In this paper, a basic study was conducted on the development of public services using micro-electric vehicle based on the constituent factors of user satisfaction. The survey includes: ① 'Analytic Hierarchy Process (AHP) for selecting the priority factors of user satisfaction of micro-electric vehicles', ② 'A survey of micro-electric vehicles image' to collect data in advance for providing users' preferences and transportation services for micro-electric vehicles, ③ In order to investigate the user satisfaction level of users who actually operated micro-electric vehicles, the order of 'user satisfaction survey of micro-electric vehicle drivers' was conducted. In the Analytic Hierarchy Process (AHP) analysis, it was found that users regarded as important in the order of 'user utilization data', 'vehicle movement data', and 'charging service data'. In the micro-electric vehicle image survey, users perceived micro-electric vehicles more positively in terms of "safety", 'durability', 'Ride comfort', 'design', 'MOOE (Maintenance and other operating expense)', and 'environment-friendly' when comparing micro-electric vehicles with electric motorcycles. In the survey on the user satisfaction of micro-electric vehicle drivers, the use of micro-electric vehicle did not directly affect work performance efficiency, and there was an experience of being disadvantaged on the road due to the size of the micro-electric vehicle, and driving in a cluster of micro-electric vehicle for outdoor advertisements. The city's public relations effect was great, but it was concerned about safety. In the future, based on the results of this study, we plan to build a user satisfaction structural equation model, preemptively discover feedback R&D for micro-electric vehicle utilization services in the public field, and actively seek to discover new public mobility support services.

• Journal of the Korean earth science society
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• v.42 no.5
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• pp.536-555
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• 2021

Sea-surface wind is an important variable in ocean-atmosphere interactions, leading to the changes in ocean surface currents and circulation, mixed layers, and heat flux. With the development of satellite technology, sea-surface winds data retrieved from scatterometer observation data have been used for various purposes. In a complex marine environment such as the Korean Peninsula coast, scatterometer-observed sea-surface wind is an important factor for analyzing ocean and atmospheric phenomena. Therefore, the validation results of wind accuracy can be used for diverse applications. In this study, the sea-surface winds derived from ASCAT (Advanced SCATterometer) mounted on MetOp-A/B (METeorological Operational Satellite-A/B) were validated compared to in-situ wind measurements at 16 marine buoy stations around the Korean Peninsula from January to December 2020. The buoy winds measured at a height of 4-5 m from the sea surface were converted to 10-m neutral winds using the LKB (Liu-Katsaros-Businger) model. The matchup procedure produced 5,544 and 10,051 collocation points for MetOp-A and MetOp-B, respectively. The root mean square errors (RMSE) were 1.36 and 1.28 m s^-1, and bias errors amounted to 0.44 and 0.65 m s^-1 for MetOp-A and MetOp-B, respectively. The wind directions of both scatterometers exhibited negative biases of -8.03° and -6.97° and RMSE values of 32.46° and 36.06° for MetOp-A and MetOp-B, respectively. These errors were likely associated with the stratification and dynamics of the marine-atmospheric boundary layer. In the seas around the Korean Peninsula, the sea-surface winds of the ASCAT tended to be more overestimated than the in-situ wind speeds, particularly at weak wind speeds. In addition, the closer the distance from the coast, the more the amplification of error. The present results could contribute to the development of a prediction model as improved input data and the understanding of air-sea interaction and impact of typhoons in the coastal regions around the Korean Peninsula.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.453-462
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• 2021

A lot of license plate data is required for car number recognition. License plate data needs to be balanced from past license plates to the latest license plates. However, it is difficult to obtain data from the actual past license plate to the latest ones. In order to solve this problem, a license plate recognition study through deep learning is being conducted by creating a synthetic license plates. Since the synthetic data have differences from real data, and various data augmentation techniques are used to solve these problems. Existing data augmentation simply used methods such as brightness, rotation, affine transformation, blur, and noise. In this paper, we apply a style transformation method that transforms synthetic data into real-world data styles with data augmentation methods. In addition, real license plate data are noisy when it is captured from a distance and under the dark environment. If we simply recognize characters with input data, chances of misrecognition are high. To improve character recognition, in this paper, we applied the DeblurGANv2 method as a quality improvement method for character recognition, increasing the accuracy of license plate recognition. The method of deep learning for license plate detection and license plate number recognition used YOLO-V5. To determine the performance of the synthetic license plate data, we construct a test set by collecting our own secured license plates. License plate detection without style conversion recorded 0.614 mAP. As a result of applying the style transformation, we confirm that the license plate detection performance was improved by recording 0.679mAP. In addition, the successul detection rate without image enhancement was 0.872, and the detection rate was 0.915 after image enhancement, confirming that the performance improved.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.2
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• pp.124-134
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• 2021

Water in the Mulgol pond on Dokdo (island), Korea, was historically used for drinking water, but now it has been no longer used for this purpose due to regionally low water quality. Since 2007, this pond has been covered with a metal lid to protect from pollutants of seabirds, indicating limited light penetration into the Mulgol pond. Here, we investigated water quality in the pond and potential relationships of nitrogen components and microbes in May, June, August, and November 2020. The source salinity ranged from 1.39 to 1.57 psu. Suspended solids (0.8~5.1 mg L^-1) and chlorophyll-a (<0.01~0.49 ㎍ L^-1) remained low. The concentration of dissolved inorganic nitrogen (DIN) was between 35.9 and 47.2 mg L^-1. Thus, water in the Mulgol pond proves to be brackish water with low chlorophyll-a and high nutrients. This unique environment may be established by limited light intensity, sea fog (or seawater), and fecal pellets from many seabirds. Although the light source (800~8000 lux) was exposed to the four subsamples, chlorophyll-a concentrations were below <0.5 ㎍ L^-1 during the incubation periods. This result suggests that the biomass of phytoplankton does not increase along with an increase in light intensity. Furthermore, the content of nitrate constituted more than 90% of DIN, and a significant negative correlation between nitrate concentration and bacterial abundance was shown in May and June 2020 during the light exposure experiments (R=-0.762, p<0.05). Thus, it is possible that bacteria may be a significant agent to reduce nitrate concentration in the Mulgol pond, the relationship between nitrate concentration and bacterial abundance may vary seasonally.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.507-517
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• 2018

The probability of T/S cargo volume to decrease is the most notable problem associated with inappropriate mix of terminal operators in Busan port. Other problems include, the deterioration of the national carriers' competitiveness from non-operation of own terminal, excessively high proportion of financial operators in the engagement of operation which may result in their passiveness in timely investment, additional cost burden to carriers' in the handling inter-terminal T/S cargo transportation and inefficiency in terminal operation by the multiplicity of operators proved to be same recognized as so through the analysis. Therefore, in order to provide solutions for the problems and to strengthen Busan port's competitiveness, this research suggests the restructuring of operators mix as follows. To achieve sustainable growth of T/S cargo, global carriers' participation in terminal operation should be of utmost priority. To enhance the operational efficiency, the operators should be integrated. Similarly, the integration of operators will play a key role in verifying that national carriers' own terminal operation is an important factor in raising its competence. Finally, BPA's active engagement in the entire operation of port is also critical in public-oriented operation of the port. Whereas in the interactive analysis by taking the merits of Busan port into consideraion, global carrier's participation in operation, integration of operators and BPA's engagement in operation proved to contribute to the increase of T/S cargo and strengthening of operational efficiencies of Busan port.

• Journal of the Korean Geotechnical Society
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• v.35 no.8
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• pp.43-56
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• 2019

This research has been conducted to suggest an estimation equation of compression index to be practically applied to the southeastern areas by finding out physical and mechanical characteristics of 229 points on the southeastern coast areas (Busan area: 78 points, Gimhae area: 103 points, Geoje area: 18 points, Changwon area: 30 points) through indoor tests and analyzing its relation to the compression index. From the results, we could not only find out correlation between natural water content, liquid limit and initial void ratio versus compression index for soft ground on each of the southeastern coast areas, but also an integrated correlation equation of the southeastern coast areas. In addition, we have performed a comparative analysis of the existing estimated equation of compression index and that found in this paper. As a result, the existing estimated equation suggested by foreign researchers has shown considerable error to be applied to the soft ground on the southeastern coast areas in Korea. The estimated equation of compression index with the water content out of the existing estimated equations has shown minimum 10.8% to maximum 48.1% of error rate, minimum 13.4% to maximum 288.5% of error rate with liquid limit or minimum 9.4% to maximum 211.4% of error rate with initial void ratio. On the other hand, error rates calculated with the estimated equations of compression index from this research have shown minimum 10.5% to maximum 13.4% with water content, minimum 11.6% to maximum 21.3 with liquid limit or minimum 7.1% to maximum 11.7% with initial void ratio, for better results than those with existing estimated equations. In addition, relation between compression index and expansion index has shown Cs = (1/5 ~ 1/12)Cc similar to the existing relation of Cs = (1/5 ~ 1/10)Cc.

• Korean journal of applied entomology
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• v.58 no.3
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• pp.183-187
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• 2019

To establish the cooperative monitoring network which can investigate introductions or outbreaks of high risk insect pests into Korea, seven universities, Gyeongsang National University, Kunsan National University, Seoul National University, Sunchon National University, Andong National University, Jeju National University, and Chungbuk National University, carried out seven regions' monitoring about nine high risk insect pests, Aceria diospyri, Bactrocera dorsalis, Bactrocera minax, Bactrocera tsuneonis, Cydia pomonella, Lobesia botrana, Proeulia sp., Solenopsis invicta, Stephanitis takeyai, from June to October in 2018. A total of 7,560 traps/visual scouting were investigated in 315 points of 105 local sites of seven regions, resulting the nine species, A. diospyri, B. dorsalis, B. minax, B. tsuneonis, C. pomonella, L. botrana, Proeulia sp., S. invicta, and S. takeyai, were not detected. From this study, we established the nationwide monitoring system which can early detect high risk insect pests and secured a bridgehead for monitoring invasive insect pests passing the border.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.36-49
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• 2019

The objectives of this study were to extract "Field Survey Based Infection Tree of Pine Wilt Disease(FSB_ITPWD)" and "Object Classification Based Infection Tree of Pine Wilt Disease(OCB_ITPWD)" from the Research Forest at Kangwon National University, and evaluate the spatial distribution characteristics and occurrence intensity of wood infested by pine wood nematode. It was found that the OCB optimum weights (OCB) were 11 for Scale, 0.1 for Shape, 0.9 for Color, 0.9 for Compactness, and 0.1 for Smoothness. The overall classification accuracy was approximately 94%, and the Kappa coefficient was 0.85, which was very high. OCB_ITPWD area is approximately 2.4ha, which is approximately 0.05% of the total area. When the stand structure, distribution characteristics, and topographic and geographic factors of OCB_ITPWD and those of FSB_ITPWD were compared, age class IV was the most abundant age class in FSB_ITPWD (approximately 55%) and OCB_ITPWD (approximately 44%) - the latter was 11% lower than the former. The diameter at breast heigh (DBH at 1.2m from the ground) results showed that (below 14cm) and (below 28cm) DBH trees were the majority (approximately 93%) in OCB_ITPWD, while medium and (more then 30cm) DBH trees were the majority (approximately 87%) in FSB_ITPWD, indicating different DBH distribution. On the other hand, the elevation distribution rate of OCB_ITPWD was mostly between 401 and 500m (approximately 30%), while that of FSB_ITPWD was mostly between 301 and 400m (approximately 45%). Additionally, the accessibility from the forest road was the highest at "100m or less" for both OCB_ITPWD (24%) and FSB_ITPWD (31%), indicating that more trees were infected when a stand was closer to a forest road with higher accessibility. OCB_ITPWD hotspots were 31 and 32 compartments, and it was highly distributed in areas with a higher age class and a higher DBH class.

• Korean Journal of Child Education & Care
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• v.19 no.2
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• pp.177-196
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• 2019

Objective: This study aims to analyze research trends related to software education for young children, focusing on studies published in Korea from 2016 to 2019 March. Methods: A total of 26 research publications on software education for young children, searched from Korea Citation Index and Research Information Sharing Service were identified for the analysis. The trend in these publications was classified and examined respectively by publication dates, types of publications, and the fields of study. To investigate a means of research, the analysis included key topics, types of research methods, and characteristics of the study variables. Results: The results of the analysis show that the number of publications on the topic of software education for young children has increased over the three years, of which most were published as a scholarly journal article. Among the 26 research studies analyzed, 16 (61.5%) are related to the field of early childhood education or child studies. Key topics and target subjects of the most research include the curriculum development of software education for young children or the effectiveness of software education on 4- and 5-year-old children. Most of the analyzed studies are experimental research designs or in the form of literature reviews. The most frequently studied research variable is young children's cognitive characteristics. For the studies that employ educational programs, the use of a physical computing environment is prevalent, and the most frequently used robot as a programming tool is "Albert". The duration of the program implementation varies, ranging from 5 weeks to 48 weeks. In the analyzed research studies, computational thinking is conceptualized as a problem-solving skill that can be improved by software education, and assessed by individual instruments measuring sub-factors of computational thinking. Conclusion/Implications: The present study reveals that, although the number of research publications in software education for young children has increased, the overall sufficiency of the accumulated research data and a variety of research methods are still lacking. An increased interest in software education for young children and more research activities in this area are needed to develop and implement developmentally appropriate software education programs in early childhood settings.