• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.209-218
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• 2024

The National Institute of Agricultural Sciences (NAS) operates in-house long-range climate forecasting system to support the agricultural use of climate forecast data. This system, developed through collaborative research with Pusan National University, is based on the PNU/RDA Coupled General Circulation Model (CGCM) and includes the regional climate model WRF (Weather Research and Forecasting). It generates detailed climate forecast data for periods ranging from 1 to 6 months, covering 20 key variables such as daily maximum, minimum, and average temperatures, precipitation, and agricultural meteorological elements like solar radiation, soil moisture, and ground temperature-factors essential for agricultural forecasting. The data are provided at a daily temporal resolution with a spatial resolution of a 5km grid, which can be used in point form (interpolated) or averaged across administrative regions. The system's seasonal temperature and precipitation forecasts align closely with observed climatological data, accurately reflecting spatial and topographical influences, confirming its reliability. These long-range forecasts from NAS are expected to offer valuable insights for agricultural planning and decision-making. The detailed forecast data can be accessed through the Climate Change Assessment Division of NAS.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.94-108
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• 2010

The purpose of this study is to provide data for the restoration of 'Yongyun(龍淵)' and 'Hwahongmun(華虹門)' through an investigation of the vicinity of their original landscapes at the time of construction of Hwaseong in Suwon and through tracing the transformative process of the environments of this vicinity. The results are as follows; As identified by 'Yongyunjung(龍淵亭)' and 'Yongdugak(龍頭閣)', other names of Yongyun, 'Banghwasuryujung(訪花隨柳亭)', which was built on 'Yongduam', is a facility whose place identity is highlighted with a sense of unity with Yongyun. The south lakefront of Yongyun, bordering Banghwasuryujung, has boundaries that make the best use of the natural geographical features of Yongduam while the current circumference of Yongyun is comparatively shorter than its original state. The size of 'Joongdo(中島)', however, seems to be an example of apparent over-design complement and reorganize 'Joongdo', which had been restored larger than its original state at the time of restoration in the 1970s. The depth of 'Yongyun' was created to be lower than the actual depth, without consideration for its initial depth, as soil was accumulated through continuous flooding after it was created. It is assumed that the original drains which were installed about 10m inside the lake were created facing the stream. As regards the planting environment, a circular planting of willows was made in the outskirts of 'Yongyun', except the 'Yongduam' which is a pure forest, and a mix of 'Pinus densiflora', shrubbery and deciduous broad leaf trees was planted in 'Joongdo'. Of the plants growing in the area of this study, plant species introduced to Korea after Hwaseong was constructed are found, most of which provide interest and attraction. The old pine trees growing in a group once grew in the castle areas of the vicinity even in the 1920s, the period of Japanese occupation, but they disappeared from the area in the aftermath of subsequent urban development and the Korean War. Although restored to the site, the number and space taken up by these trees are insignificant compared to those of the original environment. On the basis of these results, the following is considered necessary for the true restoration of the vicinity of 'Yongyun' and 'Hwahongmun': First, the grounds of 'Yongyun' should be dredged deeply enough to expose the bedrock and should be recreated in the rough outline of a half moon by extension to the southwest toward 'Yongduam' and 'Hwahongmun', and the size of 'Joongdo' should be significantly reduced. Secondly, considering that most plant species, except the pine trees and wild trees in 'Yongduam', are non-native plants introduced in order to provide such attractions such as the appreciation of scenic areas, they should be replaced with native species, mainly with the pine trees which were utilized during the construction of Hwaseong. The weeping willows planted in the 'middle-island' should be relocated to the outskirts of 'Yongyun', and replaced with pine trees as the major trees and maple trees or deciduous broadleaf trees to fill in the gaps. Thirdly, exotic species such as the 'Pinus rigida' planted in a group around 'Banghwasuryujung' and 'Bugammun' and 'Pinus strobus' planted in the vicinity of Hwahongmun' should be removed.

• Economic and Environmental Geology
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• v.50 no.4
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• pp.257-266
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• 2017

Batch experiments were performed to develop the method for the pH reduction of recycled aggregate by using $scCO_2$ (supercritical $CO_2$), maintaining the pH of extraction water below 9.8. Three different aggregate types from a domestic company were used for the $scCO_2$-water-recycled aggregate reaction to investigate the low pH maintenance of aggregate during the reaction. Thirty five gram of recycled aggregate sample was mixed with 70 mL of distilled water in a Teflon beaker, which was fixed in a high pressurized stainless steel cell (150 mL of capacity). The inside of the cell was pressurized to 100 bar and each cell was located in an oven at $50^{\circ}C$ for 50 days and the pH and ion concentrations of water in the cell were measured at a different reaction time interval. The XRD and SEM-EDS analyses for the aggregate before and after the reaction were performed to identify the mineralogical change during the reaction. The extraction experiment for the aggregate was also conducted to investigate the pH change of extracted water by the $scCO_2$ treatment. The pH of the recycled aggregate without the $scCO_2$ treatment maintained over 12, but its pH dramatically decreased to below 7 after 1 hour reaction and maintained below 8 for 50 day reaction. Concentration of $Ca^{2+}$, $Si^{4+}$, $Mg^{2+}$ and $Na^+$ increased in water due to the $scCO_2$-water-recycled aggregate reaction and lots of secondary precipitates such as calcite, amorphous silicate, and hydroxide minerals were found by XRD and SEM-EDS analyses. The pH of extracted water from the recycled aggregates without the $scCO_2$ treatment maintained over 12, but the pH of extracted water with the $scCO_2$ treatment kept below 9 of pH for both of 50 day and 1 day treatment, suggesting that the recycled aggregate with the $scCO_2$ treatment can be reused in real construction sites.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.67-72
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• 2005

To investigate the feasibility of a new concept of storing Liquefied Natural Gas (LNG) in a lined hard rock cavern, and to develop essential technologies for constructing underground LNG storage facilities, a small pilot plant storing liquid nitrogen (LN2) has been constructed at the Korea Institute of Geoscience and Mineral Resources (KIGAM). The LN2 stored in the cavern will subject the host rock around the cavern to very low temperatures, which is expected to cause the development of an ice ring and the change of ground condition around the storage cavern. To investigate and monitor changes in ground conditions at this pilot plant site, geophysical, hydrogeological, and rock mechanical investigations were carried out. In particular, geophysical methods including borehole radar and three-dimensional (3D) resistivity surveys were used to identify and monitor the development of an ice ring, and other possible changes in ground conditions resulting from the very low temperature of LN2 in the storage tank. We acquired 3D resistivity data before and after storing the LN2, and the results were compared. From the 3D images obtained during the three phases of the resistivity monitoring survey, we delineated zones of distinct resistivity changes that are closely related to the storage of LN2. In these results, we observed a decrease in resistivity at the eastern part of the storage cavern. Comparing the hydrogeological data and Joint patterns around the storage cavern, we interpret this change in resistivity to result from changes in the groundwater flow pattern. Freezing of the host rock by the very low temperature of LN2 causes a drastic change in the hydrogeological conditions and groundwater flow patterns in this pilot plant.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.795-805
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• 2021

In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m³/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.110-120
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• 2005

For utilizing vitrification to treat low and intermediate level waste, industrial pilot plant was designed and constructed in October 1999 at Daejon, Korea through the joint research program among NETEC, MOBIS and SGN. More than 70 tests were performed on simulated IER, DAW etc. including key nuclide surrogate(Cs, Co); this plant has been shown to vitrify the target waste effectively and safely, however, some dust are generated from the HTF(High Temperature Filter) as a secondary waste. In case of long term operation, it is also concerned that pipe plugging can be occurred due to deposited dust in cooling pipe namely, connecting pipe between CCM(Cold Crucible Melter) and HTF. In this regard, we have developed the special complementary system of the off-gas treatment system to recycle the dust from HTF to CCM and to remove the interior dust of cooling pipe. Main concept of the dust recycling is to feed the dust to the CCM as a slurry state; this system is regarded as of an important position in the viewpoint of volume reduction, waste disposal cost and glass melt control in CCM. The role of DRS(Dust Recycling System) is to recycle the major glass components and key nuclides; this system is served to lower glass viscosity and increase waste solubility by recycling B, Na, Li components into glass melt and also to re-entrain and incorporate into glass melt like Cs, Co. Therefore dust recycling is helpful to control the molten glass; it is unnecessary to consider a separate dust treatment system like a cementation equipment. The effects of Dust Cleaner are to prevent the pipe plugging due to dust and to treat the deposited dust by raking the dust into CCM. During the pilot vitrification test, overall performance assessment was successfully performed; DRS and Dust Cleaner are found to be useful and effective for recycling the dust from HTF and also removing the dust in cooling pipe. The obtained operational data and operational experiences will be used as a basis of the commercial facility.

• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.13-28
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• 2023

This study examines the process of project promotion in Busan, which introduced the private participation-type consultative body for the first time in the country in the promotion stage of the private-initiated park development project, and introduced flexible application of the system and differentiated policy elements in the implementation process, and examines the operational characteristics and we tried to analyze performance, etc. As a result of the analysis, first, the preferred bidder was selected by introducing a mixed method in the project method, which is an independent project method that cannot be seen in other local governments. Second, by specifying guidelines considering the characteristics of each park and detailed guidelines such as the location, area, and maximum height of non-park facilities, criteria for establishing a rational development plan utilizing regional identity and the basis of evaluation standards were laid. Third, in the project process, transparency was secured through the delegation-type roundtable, in which the private sector performs the functions and roles of key actors, thereby preventing disputes such as suspicion of preferential treatment. Fourth, in order to improve the quality of park facilities to be donated and to secure design adequacy, after approval of the implementation plan, a general planner was introduced and construction project management (design stage) services were performed to promote efficient implementation and specialization of luxury parks in the region. As a result, the city of Busan carried out the project efficiently by conserving 5 parks from sunset, a park area of 2.25km², and reducing land compensation and park construction costs by KRW 740 billion. Reinforcement of the public nature of the private-initiated park development project was suggested. However, due to the application of these systems and verification procedures, the project period is prolonged, and park services are delayed along with the financial burden on private operators.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.