• Journal of the Korea Convergence Society
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• v.12 no.5
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• pp.167-172
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• 2021

In the situation where expectations for the growth potential of the domestic offshore wind market are increasing due to the bright growth prospect of the global offshore wind market and the motivated plan of the Korean government, domestic and foreign literature on the direction of offshore wind power generation are examined for the successful development of domestic offshore wind power, the introduction of offshore wind power is diagnosed, and improvement plans are presented for the wind power-related system being promoted by the government. In addition, practical support measures are suggested to foster related SMEs. The results of the study are as follows. First, as technology development is mainly focused on large corporations, the development capacity of small and medium manufacturing industry is very low. Therefore, it is necessary to establish and operate a core center led by government agencies to provide technical support with the initiative of national research institutes and large corporations, and universities and national research institutes should strengthen the independence of small and medium-sized enterprises through training and research and development of professional manpower. Second, as a result of the survey on the practical support plan of the company, it was found that there is a need for various support for technology development and commercialization of produced parts.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1255-1263
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• 2021

While it could become an alternative water resource, fog could undermine traffic safety and operational performance of infrastructures. To reduce such adverse impacts, it is necessary to have spatially continuous fog risk information. In this work, tree-based machine-learning models were developed in order to quantify fog risks with routine meteorological observations alone. The Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGB), and Random Forests (RF) were chosen for the regional fog models using operational weather and visibility observations within the Jeollabuk-do province. Results showed that RF seemed to show the most robust performance to categorize between fog and non-fog situations during the training and evaluation period of 2017-2019. While the LGB performed better than in predicting fog occurrences than the others, its false alarm ratio was the highest (0.695) among the three models. The predictability of the three models considerably declined when applying them for an independent period of 2020, potentially due to the distinctively enhanced air quality in the year under the global lockdown. Nonetheless, even in 2020, the three models were all able to produce fog risk information consistent with the spatial variation of observed fog occurrences. This work suggests that the tree-based machine learning models could be used as tools to find locations with relatively high fog risks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.58-76
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• 2019

As the number of reported injuries has tended to increase over time, large hospitalization expenditure from excessive medical treatments and hospitalization, and insurance frauds associated with moral hazard in minor collisions have caused a global societal problem. Many occupants of rear-ended vehicles involved in rear-end collisions complain of whiplash injury, which is also known as neck injury, without any anatomical and radiological evidence. With only clinical symptoms, stating that a whiplash injury is a type of injury defined by the Abbreviated Injury Scale would be difficult. Therefore, this study focuses on minor rear-end collisions, where the rear-ender vehicle collides with the rear-ended vehicle at rest. The mathematics dynamic model is employed to simulate a total of 100 rear-end collision scenarios based on various weights and collision speeds and identify how the weights and speeds of both vehicles influence the risk of whiplash injury in occupants involved in minor rear-end collisions. The possibility of an injury is very high when the same-weight vehicles are involved in accidents at collision speeds of 15 km/h or higher. The possibilities are 36% and 84% with collision speeds of 15 km/h and 20 km/h, respectively, if weights are disregarded.

• Clean Technology
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• v.24 no.4
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• pp.269-274
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• 2018

In this study, Life Cycle Assessment (LCA) of wet tissue manufacturing process was performed. The wet tissue manufacturing process consists of preparation of wetting agent (chemical liquid), impregnation of nonwoven fabric into wetting agent and primary and secondary packaging. Data and information were collected on the input and output of the actual process from a certain company and the database of the Korea Ministry of Environment and some foreign countries (when Korean unavailable) were employed to connect the upper and the lower process flow. Based on the above and the potential environmental impacts of the wet tissue manufacturing process were calculated. As a result of the characterization, Ozone Layer Depletion (OD) is 3.46.E-06 kg $CFC_{11}$, Acidification (AD) is 5.11.E-01 kg $SO_2$, Abiotic Resource Depletion (ARD) is $3.52.E+00\;1yr^{-1}$, Global Warming (GW) is 1.04.E+02 kg $CO_2$, Eutrophication (EUT) is 2.31.E-02 kg ${PO_4}^{3-}$, Photochemical Oxide Creation (POC) was 2.22.E-02 kg $C_2H_4$, Human Toxicity (HT) was 1.55.E+00 kg 1,4 DCB and Terrestrial Ecotoxicity (ET) was 5.82.E-04 kg 1,4 DCB. In order to reduce the environmental impact of the manufacturing process, it is necessary to improve the overall process as other general cases and change the raw materials including packaging materials with less environmental impact. Conclusively, the energy consumed in the manufacturing process has emerged as a major issue, and this needs to be reconsidered other options such as alternative energy. Therefore, it is recommended that a process system should be redesigned to improve energy efficiency and to change to an energy source with lower environmental impact. Due to the nature of LCA, the final results of this study can be varied to some extent depending on the type of LCI DB employed and may not represent of all wet tissue manufacturing processes in the current industry.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1079-1089
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• 2018

The majority of existing studies for quantifying uncertainties in climate change impact assessments suggest only the uncertainties of each stage, and not the total uncertainty and its propagation in the whole procedure. Therefore, this study has proposed a new method, the Uncertainty Delta Method (UDM), which can quantify uncertainties using the variances of projections (as the UDM is derived from the first-order Taylor series expansion), to allow for a comprehensive quantification of uncertainty at each stage and also to provide the levels of uncertainty propagation, as follows: total uncertainty, the level of uncertainty increase at each stage, and the percentage of uncertainty at each stage. For quantifying uncertainties at each stage as well as the total uncertainty, all the stages - two emission scenarios (ES), three Global Climate Models (GCMs), two downscaling techniques, and two hydrological models - of the climate change assessment for water resources are conducted. The total uncertainty took 5.45, and the ESs had the largest uncertainty (4.45). Additionally, uncertainties are propagated stage by stage because of their gradual increase: 5.45 in total uncertainty consisted of 4.45 in emission scenarios, 0.45 in climate models, 0.27 in downscaling techniques, and 0.28 in hydrological models. These results indicate the projection of future water resources can be very different depending on which emission scenarios are selected. Moreover, using Fractional Uncertainty Method (FUM) by Hawkins and Sutton (2009), the major uncertainty contributor (emission scenario: FUM uncertainty 0.52) matched with the results of UDM. Therefore, the UDM proposed by this study can support comprehension and appropriate analysis of the uncertainty surrounding the climate change impact assessment, and make possible a better understanding of the water resources projection for future climate change.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.23-30
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• 2019

The KVN(Korean VLBI Network)-style simultaneous multi-frequency receiving mode is demonstrated to be promising for mm-VLBI observations. Recently, other Very long baseline interferometry (VLBI) facilities all over the globe start to implement compatible optics systems. Simultaneous dual/multi-frequency VLBI observations at mm wavelengths with international baselines are thus possible. In this paper, we present the results from the first successful simultaneous 22/43 GHz dual-frequency observation with KaVA(KVN and VERA array), including images and astrometric results. Our analysis shows that the newly implemented simultaneous receiving system has brought a significant extension of the coherence time of the 43 GHz visibility phases along the international baselines. The astrometric results obtained with KaVA are consistent with those obtained with the independent analysis of the KVN data. Our results thus confirm the good performance of the simultaneous receiving systems for the nonKVN stations. Future simultaneous observations with more global stations bring even higher sensitivity and micro-arcsecond level astrometric measurements of the targets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.21-27
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• 2019

R-404A, which is used widely in small-scale ice makers, is scheduled to be phased out because of its high global warming potential. In this study, drop-in tests were conducted using R-448A and R-449A, which replace R-404A, to modify the outdoor air and supply water temperatures. The results showed that the daily ice production rate of R-404A was 5.3% higher than that of R-448A and 4.2% higher than that of R-449A. This was attributed to the larger vapor density of R-404A, which resulted in a larger mass flow rate in the system. Between R-448A and R-449A, R-448A yielded a larger amount of ice at low air and water temperatures, whereas R-449A yielded a larger amount of ice at high air and water temperatures. The daily power consumption of R-404A was approximately 10% larger than those of R-448A and R-449A. The resulting COPs of R-448A and R-449A was similar, only 3.0% larger than that of R-404A. The literature survey showed that the condensation or evaporation data of R-448A or R-449A are very limited, and research on this issue is recommended.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1067-1078
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• 2018

Water resources projection typically consists of several stages including emission scenarios, global circulation models (GCMs), downscaling techniques, and hydrological models, and each stage is a source of total uncertainty in water resources projection. Several studies proposed methods to quantify the relative contribution of each stage to total uncertainty, and we call such analysis uncertainty decomposition. Uncertainty decomposition enables us to investigate the stages yielding large uncertainties and to establish the uncertainty reduction plan that reflects them. Interactions between stages is one of the important issues to be considered in uncertainty decomposition. This study suggests a new uncertainty decomposition method considering interaction effect. The proposed method has an advantage of decomposing the total uncertainty to the uncertainty from each stage considering both the main and interactions effects. We apply the proposed method to streamflow projection for Chungju Dam basin. The results show that the uncertainties from the main effects are larger than the uncertainties from interaction effects in both summer and winter. Using the proposed uncertainty decomposition method, we show that the GCM stage is the largest source of the total uncertainty in summer and the downscaling technique stage is the one in winter among the following four stages: emission scenarios, GCMs, downscaling techniques, and hydrological models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.9-18
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• 2019

The intensity and the number of days of high temperature occurrence are also high and record heat occurred. In addition, the global warming phenomenon is intensifying globally, and especially in South Korea, the urban heat island phenomenon is also occurring due to rapid urbanization due to rapid industrial development. As the temperature of the city rises, it causes problems such as the comfort of the residential living and the cooling load. In this study, the cool roof performance is evaluated according to the roof color to reduce these problems. Unlike previous studies, UAV(Unmanned Aerial Vehicle) thermal infrared camera was used to obtain the surface temperature (white, grey, green, blue, brown, black) according to the rooftop color by remote sensing technique. As a result, the surface temperature of white color was $11{\sim}20^{\circ}C$ lower than other colors. Also air conditioning temperature of white color was $1.5{\sim}4.4^{\circ}C$ lower than other colors and the digital thermometer of white color was about $1.5{\sim}3.5^{\circ}C$ lower than other colors. It was confirmed that the white cool roof performance is the best, and the UAV and the thermal infrared camera can confirm the cool roof performa.