• Journal of the Korean earth science society
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• v.43 no.2
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• pp.283-302
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• 2022

Despite the nationwide COVID-19 lockdown in China since January 23, 2020, haze days with high PM₁₀ levels of 88-98 ㎍ m^-3 occurred on February 1 and 2, 2020. During these haze days, the East Asian region was affected by a warm and stagnant air mass with positive air temperature anomalies and negative zonal wind anomalies at 850 hPa. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was used to analyze the variation of regional PM₁₀ aerosol transport in Korea due to decreased anthropogenic emissions in East Asia. The base experiment (BASE), which applies the basic anthropogenic emissions in the WRF-Chem model, and the control experiment (CTL) applied by reducing the anthropogenic emission to 50%, were used to assess uncertainty with ground-based PM₁₀ measurements in Korea. The index of agreement (IOA) for the CTL simulation was 0.71, which was higher than that of BASE (0.67). A statistical analysis of the results suggests that anthropogenic emissions were reduced during the COVID-19 lockdown period in China. Furthermore, BASE and CTL applied to zero-out anthropogenic emissions outside Korea (BASE_ZEOK and CTL_ZEOK) were used to analyze the variations of regional PM₁₀ aerosol transport in Korea. Regional PM₁₀ transport in CTL was reduced by only 10-20% compared to BASE. Synthetic weather variables may be another reason for the non-linear response to changes in the contribution of regional transport to PM₁₀ in Korea with the reduction of anthropogenic emissions in East Asia. Although the regional transport contribution of other inorganic aerosols was high in CTL (80-90%), sulfate-nitrate-ammonium (SNA) aerosols showed lower contributions of 0-20%, 30-60%, and 30-60%, respectively. The SNA secondary aerosols, particularly nitrates, presumably declined as the Chinese lockdown induced traffic.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.47-72
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• 2022

This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.1
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• pp.1-17
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• 2023

Purpose. The purpose of this study was to examine the correlation between the finish line designs and the marginal adaptation of nonprecious metal alloy coping produced by different digital manufacturing methods. Materials and methods. Nonprecious metal alloy copings were made respectively from each master model with three different methods; SLS, milling and casting by computer aided design and computer aided manufacturing (CAD-CAM). Twelve copings were made by each method resulting in 72 copings in total. The measurement was conducted at 40 determined reference points along the circumferential margin with the confocal laser scanning microscope at magnification ×150. Results. Mean values of marginal gap of laser sintered copings were 11.8 ± 7.4 ㎛ for deep chamfer margin and 6.3 ± 3.5 ㎛ for rounded shoulder margin and the difference between them was statistically significant (P < .0001). Mean values of marginal gap of casted copings were 18.8 ± 20.2 ㎛ for deep chamfer margin and 33 ± 20.5 ㎛ for rounded shoulder margin and the difference between them was significant (P = .0004). Conclusion. Within the limitation of this study, the following conclusions were drawn. 1. The variation of finish line design influences the marginal adaptation of laser sintered metal coping and casted metal coping. 2. Laser sintered copings with rounded shoulder margin had better marginal fit than deep chamfer margin. 3. Casted copings with deep chamfer margin had better marginal fit than rounded shoulder margin. 4. According to the manufacturing method, SLS system showed the best marginal fit among three different methods. Casting and milling method followed that in order.

• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.289-301
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• 2023

Forests within watersheds are essential in maintaining ecosystems and are the central infrastructure for constructing an ecological network system. However, due to indiscriminate development projects carried out over past decades, forest fragmentation and land use changes have accelerated, and their original functions have been lost. Since a forest's structural pattern directly impacts ecological processes and functions in understanding forest ecosystems, identifying and analyzing change patterns is essential. Therefore, this study analyzed structural changes in the forest landscape according to the time-series land cover changes using the FRAGSTATS model for the dam watershed of the Geum River upstream. Land cover changes in the dam watershed of the Geum River upstream through land cover change detection showed an increase of 33.12 square kilometers (0.62%) of forests and 67.26 square kilometers (1.26%) of urbanized dry areas and a decrease of 148.25 square kilometers (2.79%) in agricultural areas from the 1980s to the 2010s. The results of no-sampling forest landscape analysis within the watershed indicated landscape percentage (PLAND), area-weighted proximity index (CONTIG_AM), average central area (CORE_MN), and adjacency index (PLADJ) increased, and the number of patches (NP), landscape shape index (LSI), and cohesion index (COHESION) decreased. Identification of structural change patterns through a moving window analysis showed the forest landscape in Sangju City, Gyeongsangbuk Province, Boeun County in Chungcheongbuk Province, and Jinan Province in Jeollabuk Province was relatively well preserved, but fragmentation was ongoing at the border between Okcheon County in Chungcheongbuk Province, Yeongdong and Geumsan Counties in Chungcheongnam Province, and the forest landscape in areas adjacent to Muju and Jangsu Counties in Jeollabuk Province. The results indicate that it is necessary to establish afforestation projects for fragmented areas when preparing a future regional forest management strategy. This study derived areas where fragmentation of forest landscapes is expected and the results may be used as basic data for assessing the health of watershed forests and establishing management plans.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.1-14
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• 2022

To alleviate the urban heat island phenomenon, this study aims to quantitatively analyze the effects of neighborhood green spaces on the improvement of the thermal environment based on detailed scenarios of five types of green spaces, including parks, pocket parks, parking lot greening, roadside planting, and rooftop-wall greening. The ENVI-met 4.4.6v model, a microclimate simulation program, was used to analyze the effects of green spaces. As a result, it was found that the air temperature decreased as the planting density of the park increased, but the thermal comfort index PET, which is the degree of heat sensation felt by humans, was not directly proportional to temperature. The establishment of a pocket park reduced air temperature up to a radius of 56m, while the range of temperature reduction increased by about 12.5% when three additional pocket parks were established at 250m intervals. Unlike the air temperature, PET was only affected in the vicinity of the planted area, so there was no significant difference in the thermal comfort of the surrounding environment due to the construction of pocket parks. Changing the surface pavement from asphalt to lawn blocks and implementing rooftop or wall greening did not directly act as solar shading but positively affected air temperature reduction; PET showed no significant difference. Roadside planting showed a higher air temperature reduction effect as the planting interval was narrower, but PET was not directly proportional to tree density. In the case of shrub planting under trees, it did not significantly affect the air temperature reduction but positively affected the improvement of thermal comfort. This study can outline strategies for constructing neighborhood green spaces to solve the urban heat island phenomena and establish detailed strategies for efficient thermal environment improvements.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.1-11
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• 2016

With increasing interest, there have been studies on LiDAR(Light Detection And Ranging)-based DEM(Digital Elevation Model) to acquire three dimensional topographic information. For producing LiDAR DEM with better accuracy, Filtering process is crucial, where only surface reflected LiDAR points are left to construct DEM while non-surface reflected LiDAR points need to be removed from the raw LiDAR data. In particular, the changes of input values for filtering algorithm-constructing parameters are supposed to produce different products. Therefore, this study is aimed to contribute to better understanding the effects of the changes of the levels of GroundFilter Algrothm's Mean parameter(GFmn) embedded in FUSION software on the accuracy of the LiDAR DEM products, using LiDAR data collected for Hwacheon, Yangju, Gyeongsan and Jangheung watershed experimental area. The effect of GFmn level changes on the products' accuracy is estimated by measuring and comparing the residuals between the elevations at the same locations of a field and different GFmn level-produced LiDAR DEM sample points. In order to test whether there are any differences among the five GFmn levels; 1, 3, 5, 7 and 9, One-way ANOVA is conducted. In result of One-way ANOVA test, it is found that the change in GFmn level significantly affects the accuracy (F-value: 4.915, p<0.01). After finding significance of the GFmn level effect, Tukey HSD test is also conducted as a Post hoc test for grouping levels by the significant differences. In result, GFmn levels are divided into two subsets ('7, 5, 9, 3' vs. '1'). From the observation of the residuals of each individual level, it is possible to say that LiDAR DEM is generated most accurately when GFmn is given as 7. Through this study, the most desirable parameter value can be suggested to produce filtered LiDAR DEM data which can provide the most accurate elevation information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4C
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• pp.247-254
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• 2006

Online testing method is one of the numerical experiment methods using experimental information for a numerical analysis directly. The method has an advantage in that analysis can be conducted without using an idealized mechanical model, because mechanical properties are updated from element test for a numerical analysis in real time. The online testing method has mainly been used for the geotechnical seismic engineering, whose major target is sand. A testing method that may be applied to a consolidation problem has recently been developed and laboratory and field verifications have been tried. Although related research thus far has mainly used a method to update average reaction for a numerical analysis by positioning an element tests at the center of a consolidation layer, a weakness that accuracy of the analysis can be impaired as the thickness of the consolidation layer becomes more thicker has been pointed out regarding the method. To clarify the effectiveness and possible analysis scope of the online testing method in relation to the consolidation problem, we need to review the results by applying experiment conditions that may completely exclude such a factor. This research reviewed the results of the online consolidation test in terms of reproduction of the consolidation settlement and the dissipation of excess pore water pressure of a clay specimen by comparing the results of an online consolidation test and a separated-type consolidation test carried out under the same conditions. As a result, the online consolidation test reproduced the change of compressibility according effective stress of clay without a huge contradiction. In terms of the dissipation rate of excess pore water pressure, however, the online consolidation test was a little faster. In conclusion, experiment procedure needs to improve in a direction that hydraulic conductivity can be updated in real time so as to more precisely predict the dissipation of excess pore water pressure. Further research or improvement should be carried out with regard to the consolidation settlement after the end of the dissipation of excess pore water pressure.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.