• Journal of Wetlands Research
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• v.23 no.4
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• pp.287-295
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• 2021

As facilities such as dam reservoir wetlands and agricultural irrigation reservoir wetlands are built, sedimentation occurs over time through erosion, sedimentation transport, and sediment deposition. Sedimentation issues are very important for the maintenance of reservoir wetlands because long-term sedimentation of sediments affects flood and drought control functions. However, research on resignation has been estimated mainly by empirical formulas due to the lack of available data. The purpose of this study was to calculate and compare the sediment deposition rate by developing a multiple regression model along with actual data and empirical formulas. In addition, it was attempted to identify potential causes of collapse by applying it to 64 reservoir wetlands that suffered flood damage due to the long rainy season in 2020 due to reservoir wetland sedimentation and aging. For the target reservoir, 10 locations including the GaGog reservoir located in Miryang city, Gyeongsangnam province in South Korea, where there is actual survey information, were selected. A multiple regression model was developed in consideration of physical and climatic characteristics, and a total of four empirical formulas and sediment deposition rate were calculated. Using this, the error of the sediment deposition rate was compared. As a result of calculating the sediment deposition rate using the multiple regression model, the error was the lowest from 0.21(m³km²/yr) to 2.13(m³km²/yr). Therefore, based on the sediment deposition rate estimated by the multi-regression model, the change in the available capacity of reservoir wetlands was analyzed, and the effective storage capacity was found to have decreased from 0.21(%) to 16.56(%). In addition, the sediment deposition rate of the reservoir where the overflow damage occurred was relatively higher than that of the reservoir where the piping damage occurred. In other words, accumulating sediment deposition rate at the bottom of the reservoir would result in a lack of acceptable effective water capacity and reduced reservoir flood and drought control capabilities, resulting in reservoir collapse damage.

• Journal of Environmental Impact Assessment
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• v.30 no.6
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• pp.339-354
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• 2021

The purpose of this study is to provide valuable information and data by analyzing the environmental status and potential forrenewable energy projects (or plans) based on environmental assessment (EA) data, so that more objective and scientific environmental assessments can be conducted. The study also suggests regional directions that could satisfy the goals of nature conservation and renewable energy. Based on the analysis of EA data that was conducted up until June 2019, the study analyzed the size, location and characteristics of both onshore wind power and onshore photovoltaic. The environmentally available potential by region was also derived by considering the main constraints and requirements related to the potential siting ofrenewable energy projects at the EA. Based on EA data, 63 out of 80 (79%) onshore wind power projects are shown to be located in mountainous areas. For onshore photovoltaic projects, a total of 7,363 projects were subjected to environmental assessment over the country. The environmentally potential area for onshore wind power, considering all the environmental regulatory factors, is 2,440 km². For onshore photovoltaic, the environmentally available area estimated as idle farmland is 2,877 km². The distribution and characteristics of the environmentally available potential of the region may be the most important factor that local governments should bear in mind in terms of promoting renewable energy development projects in the region. Based on the results of this study, even if we consider the national energy plan including the expected future increase, as well as environmental goals and socio-economic acceptance through an environmental assessment, the available resources forrenewable energy projects are not insufficient. It is possible to examine the adequacy of the target distribution rate of renewable energy sources by region taking into consideration the quantitative and scientific results such as the environmentally available potential data derived from this study.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.113-137
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• 2021

According to the clear potential of mobile banking growth, many studies related to this are being conducted, but in Korea, it is concentrated on the analysis of technical factors or consumers' intentions, behaviors, and satisfaction. In addition, even though it has a strong customer base of 20s, there are few studies that have been conducted specifically for this customer group. In order for mobile banking to take a leap forward, a strategy to secure various perspectives is needed not only through research on itself but also through research on external factors affecting mobile banking. Therefore, this study analyzes impulsiveness, credit card use, and SNS addiction among various external factors that can significantly affect mobile banking in their 20s. This study examines whether the relationship between impulsiveness and mobile banking usage depends on whether or not a credit card is used, and checks whether a customer's impulsiveness is possible by examining whether a credit card is used. Based on this, it is possible to establish new standards for classification of marketing target groups of mobile banking. After finding out the static or unsuitable relationship between whether to use a credit card and impulsiveness, we want to indirectly predict the customer's impulsiveness through whether to use a credit card or not to use a credit card. It also verifies the mediating effect of SNS addiction in the relationship between impulsiveness and mobile banking usage. For this analysis, the collected data were conducted according to research problems using the SPSS Statistics 25 program. The findings are as follows. First, positive urgency has been shown to have a significant static effect on mobile banking usage. Second, whether to use credit cards has shown moderating effects in the relationship between fraudulent urgency and mobile banking usage. Third, it has been shown that all subfactors of impulsiveness have significant static relationships with subfactors of SNS addiction. Fourth, it has been confirmed that the relationship between positive urgency, SNS addiction, and mobile banking usage has total effect and direct effect. The first result means that mobile banking usage may be high if positive urgency is measured relatively high, even if the multi-dimensional impulsiveness scale is low. The second result indicates that mobile banking usage rates were not affected by the independent variable, negative urgency, but were found to have a significant static relationship with negative urgency when using credit cards. The third result means that SNS is likely to become addictive if lack of premeditation or lack of perseverance is high because it provides instant enjoyment and satisfaction as a mobile-based service. This also means that SNS can be used as an avoidance space for those with negative urgency, and as an emotional expression space for those with high positive urgency.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.903-916
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• 2021

An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Korean Chemical Engineering Research
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• v.59 no.4
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• pp.548-556
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• 2021

This study was conducted to investigate the applicability of lignocellulosic fiber and coconut shell activated carbon (CSA) for the production of a particulate matter (PM)-reducing air-filter as raw materials to solve the environmental problems of non-woven fabrics. CSA had a good potential to use as a raw material of air-filter for reducing volatile organic compounds as well as noxious metals, and reduction capability of the CSA was 5 times higher than that of wood fiber. Natural adhesives formulated with proteinaceous wastes mostly were applied successfully to fabricate air-filters with the shape of fiberboard. The air-filter fabricated with the minimum target density of 200 kg/m³ and the maximum CSA-content of 40 wt% in fiberboard had a good manageable strength. However, the fiberboard filters was required to make vent-holes for improving an air-permeability of the filters. Size of the CSA particles was adjusted to greater than 2 mesh with the consideration of strength and formability of the fiberboard. Three-layers fiberboard that only wood fiber and the mixture of wood fiber and CSA were formed in the surface and middle layers, respectively, was determined to the optimal condition for the production of air-filters. In addition, traditional Korean paper handmade from mulberry trees (TKP) showed a good PM-reducing property as an air-filter. It is concluded that air-filtering set composed of fiberboard with vent-holes and TKP instead of conventional air-filters made with non-woven fabrics can be used as a filter for reducing the concentrations of PM, VOC and noxious metals existed in indoor and outdoor spaces.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.438-479
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• 2021

Basic information such as flora and their distribution are the key factors to consider for preserving plant diversity on a regional level. The number of plant species identified through a survey is closely related to the survey area and the number of habitats distributed within the survey area. In this study, we surveyed the flora of Mt. Maryong-san (PH) and Mt. Daeso-san (YH) located in Uljin-gun, Gyeongsangbuk-do, six and nine times, respectively. We planned to include a variety of habitats in the survey routes. As a result, we identified a total of 594 taxa composing of 112 families, 349 genera, 548 species, 10 subspecies, 34 varieties, and 2 formulas in the Mt. Maryong-san (PH) area and a total of 434 taxa composing of 89 families, 270 genera, 400 species, 9 subspecies, and 25 varieties in the Mt. Daeso-san (YH) area. Of the plants observed in the 21 habitats, the plants distributed in the transition zone around the valley and the dry grassland accounted for the highest proportion. The traditional graveyards located on the coast also served as the major habitat for the distribution of some plant species. In the two graveyards, 19 taxa of endemic plant species were surveyed. Moreover, the identified floristic target species included 1 taxon for grade V, 11 taxa for grade IV, and 24 taxa for grade III. A total of 77 taxa of naturalized plants were identified, and four of them were invasive alien plants as designated by the Ministry of Environment. The differences in the plants distributed in the area of Mt. Maryong-san (PH) and Mt. Daeso-san (YH) were mainly due to the difference in the size of each habitat distributed within the survey area. Moreover, it was judged that the entire vicinity of Mt. Daeso-san (YH) was not connected to the surrounding mountains and was an isolated area surrounded by farmland and residential areas.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.3
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• pp.205-212
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• 2021

The skin fibroblasts of different origins showed different expression levels of MMP-1 in response to TNF-α treatment or UV irradiation. We hypothesized that this is caused by polymorphism in the MMP-1 promoter region. To elucidate it, first of all, we analyzed and classified the genotype of the -1607 site of the MMP-1 promoter in 23 commercially available primary fibroblasts, and then we examined the expression of MMP-1 by TNF-α or UVB stimulation for each classified genotype. As a result of the analysis, fibroblasts with 6 1G/1G genotypes, 10 1G/2G genotypes, and 7 2G/2G genotypes were identified. Hs68 and Detroit 551 cell lines were confirmed to have 1G/2G genotypes. In the 1G/1G genotype, MMP-1 was expressed twice as high as that of the control group by TNF-α treatment, and was hardly expressed by UV light. In the case of the 1G/2G genotype, MMP-1 was expressed 2.45 fold higher by TNF-α treatment, and 1.4 fold by UV light than the control. In the case of the 2G/2G genotype, MMP-1 was expressed 1.35 fold by TNF-α treatment, and was highly expressed by 2.5 fold by ultraviolet rays compared to control. It can be estimated that MMP-1 expression is better induced in the 1G genotype by TNF-α and in the 2G genotype by UV light. In addition, it can be presumed that MMP-1 expression is increased by creating a site where the Ets transcription factor can bind by another G inserted at the -1607 position. These studies have not been conducted at all in fibroblasts in relation to skin aging, so it is an area that needs to be further studied in the future. In conclusion, since the skin is an organ that is affected by both intrinsic aging and photoaging at the same time, when analyzing the expression of MMP-1 as a target for improving skin aging, it is necessary to select cells with a genotype suitable for the experimental conditions of the study.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• 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.