• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Korean Journal of Culture and Social Issue
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• v.22 no.4
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• pp.523-541
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• 2016

Both the child's and defendant's testimonies play crucial roles in the court's ruling of a child abuse case. Thus, empirical studies examining a child's truthful report, that is, disclosure, of his or her experience and recantation of the disclosure have manifold practical implications. The objective of the present study was to examine how easily a child recants his or her testimony after witnessing and disclosing an adult engaging in a small mistake. Furthermore, this study examined whether the child's age and emotional support from his or her caregiver predict the recantation of the child's testimony. Children of age 5-8 years played with dolls with the experimenter and witnessed the experimenter breaking the doll mask. The experimenter asked the children to keep it a secret. Then the children had the first memory interview, during which the interviewer induced the child to disclose the incident. Based on the treatment conditions, some children were provided supportive feedback while other received unsupportive feedback from their primary caregivers (mother) regarding the disclosure, then were interviewed for the second time. First, the author of this study examined whether the children would recant their disclosure (whether they would deny the incident after telling the truth of about what happened to the doll), and also examined the features of the child's voluntary reports, that is, the degree of their honesty. The findings of the experiment indicated that there were age-specific differences in the frequency of recantation, meaning that older children (8-9-year-olds) showed a stronger tendency to maintain their recantation in the second interview than relatively younger children (6-7-year-olds). Furthermore, children who received supportive responses from their mothers regarding the disclosure demonstrated more honest reports compared to those who received unsupportive responses from their mothers. The findings of this study assist the understanding of the effects of social-motivational factors on the process of children disclosing the truth when voluntarily recalling a negative incident that they had experienced and provide practical implications in legal aspects.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.421-433
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• 2023

The final disposal of spent nuclear fuel(SNF) from nuclear power plants takes place in a deep geological repository. The metal canister encasing the SNF is made of cast iron and copper, and is engineered to effectively isolate radioactive isotopes for a long period of time. The SNF is further shielded by a multi-barrier disposal system comprising both engineering and natural barriers. The deep disposal environment gradually changes to an anaerobic reducing environment. In this environment, sulfide is one of the most probable substances to induce corrosion of copper canister. Stress-corrosion cracking(SCC) triggered by sulfide can carry substantial implications for the integrity of the copper canister, potentially posing a significant threat to the long-term safety of the deep disposal repository. Sulfate can exist in various forms within the deep disposal environment or be introduced from the geosphere. Sulfate has the potential to be transformed into sulfide by sulfate-reducing bacteria(SRB), and this converted sulfide can contribute to the corrosion of the copper canister. Bentonite, which is considered as a potential material for buffering and backfilling, contains oxidized sulfate minerals such as gypsum(CaSO4). If there is sufficient space for microorganisms to thrive in the deep disposal environment and if electron donors such as organic carbon are adequately supplied, sulfate can be converted to sulfide through microbial activity. However, the majority of the sulfides generated in the deep disposal system or introduced from the geosphere will be intercepted by the buffer, with only a small amount reaching the metal canister. Pyrite, one of the potential sulfide minerals present in the deep disposal environment, can generate sulfates during the dissolution process, thereby contributing to the corrosion of the copper canister. However, the quantity of oxidation byproducts from pyrite is anticipated to be minimal due to its extremely low solubility. Moreover, the migration of these oxidized byproducts to the metal canister will be restricted by the low hydraulic conductivity of saturated bentonite. We have comprehensively analyzed and summarized key research cases related to the presence of sulfates, reduction processes, and the formation and behavior characteristics of sulfides and pyrite in the deep disposal environment. Our objective was to gain an understanding of the impact of sulfates and sulfides on the long-term safety of high-level radioactive waste disposal repository.

• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.259-272
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• 2023

This study set up 49 survey areas with an area of about 400 square meters in Abies koreana natural habitat to identify the species composition and vegetation structure of the A. koreana forest in the Mt. Jiri Nation Park, conducted field surveys using phytosociological methods, and performed the cluster analysis using the Two-Way Indicator Species Analysis (TWINSPAN) and Table manipulation. Subsequently, species composition analysis using the importance value, species diversity analysis, DBH analysis, sapling analysis, and similarity analysis was conducted by each cluster type. The cluster analysis classified the A. koreana forest in Mt. Jiri into five clusters, A, B, C, D, and E. The forest was divided into two clusters, Magnolia sieboldii-Dryopteris crassirhizoma-Sasa borealis and Betula ermanii-Solidago virgaurea-Calamagrostis arundinacea. The former was classified as type A and B by Cornus controversa-Hydrangea macrophylla, and the latter was classified as type E, a typical community, and a Sorbus commixta-Rhododendron mucronulatum cluster. And the S. commixta-R. mucronulatum cluster was divided into C type and D type by Picea jezoensis-Ligularia fischeri and Ainsliaea acerifolia. Through vegetation analysis, the importance value of A. koreana, Quercus mongolica, Acer pseudosieboldianum, Fraxinus sieboldiana, and B. ermanii was highly expressed in the A. koreana forest in Mt. Jiri. Regarding species diversity, the results were similar to those reported in other studies of A. koreana forests in Mt. Jiri. The analysis of diameter at breast height (DBH) showed that A. koreana dominated all layers, and the growth of saplings was also good, indicating that the dominance of A. koreana is expected to continue for a while. However, when considering the value of biodiversity that is expected to increase and threats caused by climate change, systematic preservation and management are required to respond to various threats based on continuous monitoring.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.1-15
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• 2019

Psy's Gangnam style in 2012 showed K-pop's potential for global growth and BTS proved it by reaching three consecutive Billboard No.1. The success in the global music market brings tremendous economical and cultural power. This study is conducted for the continuous growth of K-pop music in the global music market by analyzing the musical factor of K-pop's global success. The top 20 most-viewed K-pop MV on Youtube is chosen as a research subject because Youtube is a worldwide platform that reflects global popularity. For the process of K-pop music creation, the role of the composer is expanded and many overseas producers participate in music creation. All 20 songs are created by the collective creation system and there is a consecutive collaboration between the main producers and certain artists. The top 20 most viewed K-pop songs have the musical characteristics of transnational genre convergence, hook songs, sophisticated sounds, frequent use of English lyrics, a reflection of the latest global trends, rhythm optimized for dance and clear concept. It makes the K-pop song easily remembered and familiar to overseas listeners. K-pop's healthy and fresh theme brings emotional empathy and reflects Korean sentiments. K-pop's global success is not a coincidence, but a result of continuous efforts to advance overseas. Some critics criticize K-pop's musical style is similar and it shows K-pop's limitation but K-pop progressed its musical evolution. By keeping the merits of K-pop's success factors and complementing its weak points, K-pop will continue its popularity and increase influence in the global music market.

• Korean Journal of Forensic Psychology
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• v.12 no.1
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• pp.15-33
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• 2021

In this study, we analyzed the difference in survival rates of those subject to electronic supervision of sex crimes based on the tracking of the period of recidivism and whether they were recidivism, and wanted to confirm the ability of the criminal record to predict recidivism. The criteria for recidivism were defined as cases where a conviction was confirmed due to a criminal case that occurred during the execution of electronic monitoring, and the date of recidivism was the date of occurrence of a case that was confirmed guilty. A total of 122 re-offenders were used in the analysis, and all of them were charged with electronic supervision for committing sex crimes. Studies have confirmed that the subjects commit the most recidivism within three years. In addition, in this study, the difference in survival rate between groups was analyzed after classifying mixed and sex recidivism cases. The number of members was 88 for the mixed recidivism group and 34 for the sex recidivism group. The analysis confirmed that both groups had the most recidivism within three years. There was a slight difference between the survival rate of the mixed recidivism group and the survival rate of the sex recidivism group. So the Log Rank Test and the Generalized Wilcoxon Test were conducted, but no statistically significant differences were identified(Wilcoxon statistic = 2.326, df = 1, p = .13, Log Rank = 1.345, df = 1, p = .25). Next, a Cox Regression analysis was performed to confirm the ability of the criminal record to predict recidivism. As a result, the number of criminal records(sex offense, violent crime) have been confirmed to be a good predictor of recidivism(X²=27.33, df=1, p< .001). As a result, the recidivism rate is gradually decreasing due to the implementation of the electronic monitoring. However, the duration of recidivism required by sex offenders in high-risk groups was found to be rather short. Currently, security measures against felons are being strengthened, so it is necessary to select high-risk groups. Therefore, based on the related studies, the characteristics of high-risk groups and the results of recidivism studies will be used as a basis for disposal within the criminal justice system, which will play a major role in granting objectivity.

• Journal of the Korean Regional Science Association
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• v.39 no.1
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• pp.53-66
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• 2023

Due to COVID-19, the external activities of urban residents have greatly shrunk, causing a lot of damage to the commercial district, such as a decrease in population and sales. The downturn in commercial districts means the collapse of the infrastructure of the national economy, and can have serious side effects on the local economy and individual lives. Therefore, it is necessary to look at the alley commercial area, which is closely related to the national local economy, and pay attention to the damage and stagnation of the alley commercial area where small business owners are concentrated. The purpose of this study is to classify alley commercial districts into growth commercial districts and decline commercial districts by using commercial sales time series data and DTW time series group analysis for the pre- and post-COVID-19 period. The main findings of the study are as follows. First, using the time series data on commercial sales before and after COVID-19, the alley commercial districts were divided into growth commercial districts and decline commercial districts, and it was confirmed that the distribution of growth commercial districts and decline commercial districts was regionally different. Therefore, it is necessary to actively manage commercial districts in areas where many declining commercial districts are distributed, and it is required to prepare policies for each region in consideration of the spatial distribution of declining commercial districts. Second, during the COVID-19 period, face-to-face essential industries, density of guest facilities, and population density negatively affected the sustainability of commercial districts, which is the opposite of previous studies. This is the result of empirically confirming the specificity of the COVID-19 period and the negative effects of the integrated economy, and can be used as basic data for effective commercial district management and policy preparation in the event of a national disaster in the future. Third, the characteristics of the background of the commercial district had a significant effect on the sustainability of the commercial district, and the negative effect of the attracting facilities inducing population concentration in the background area was found. This suggests that it is necessary to consider the characteristics of the background as well as the inside of the commercial district when establishing policies to revitalize the commercial district and support small business owners in a national disaster situation.

• Applied Chemistry for Engineering
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• v.34 no.2
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• pp.111-120
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• 2023

The nucleation mechanism was studied using a calcium ion selective electrode (Ca ISE) to observe the formation of CaCO₃, a representative mineral in the CO2 cycle, and to analyze the effect of the Mg/Ca-ratio and temperature on the formation of pre-nucleation cluster (PNC) and CaCO₃. As a result of the experiment, a small amount of crystal was formed. Energy dispersive X-ray spectroscopy (EDS) was used for surface element analysis, and a field emission scanning-electron microscope (FE-SEM) was used for the morphology analysis of synthesized carbonates. These results showed that various shapes of crystalline CaCO₃ (calcite, aragonite, etc.) were observed for each Mg/Ca ratio and temperature. In addition, the calibration plot obtained from Ca ISE showed information on the formation process of CaCO₃. Our results showed that as magnesium ions interfered with the binding of calcium and carbonate ions and delayed the aggregation between PNCs, the nucleation and formation of CaCO₃ were delayed. On the other hand, the temperature showed an opposite trend as compared to the effect of magnesium under our experimental conditions, indicating that temperature accelerated the formation of CaCO₃. Furthermore, the morphology of CaCO₃ clearly changed according to the Mg/Ca ratio and temperature, and it was confirmed that the two factors are very important for CaCO₃ formation in that they could affect the overall process.

• Journal of IKEEE
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• v.27 no.1
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• pp.116-121
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• 2023

In this paper, we develop a deep learning structure for a complex microbial incubator that applies deep learning prediction result information. The proposed complex microbial incubator consists of pre-processing of complex microbial data, conversion of complex microbial data structure, design of deep learning network, learning of the designed deep learning network, and GUI development applied to the prototype. In the complex microbial data preprocessing, one-hot encoding is performed on the amount of molasses, nutrients, plant extract, salt, etc. required for microbial culture, and the maximum-minimum normalization method for the pH concentration measured as a result of the culture and the number of microbial cells to preprocess the data. In the complex microbial data structure conversion, the preprocessed data is converted into a graph structure by connecting the water temperature and the number of microbial cells, and then expressed as an adjacency matrix and attribute information to be used as input data for a deep learning network. In deep learning network design, complex microbial data is learned by designing a graph convolutional network specialized for graph structures. The designed deep learning network uses a cosine loss function to proceed with learning in the direction of minimizing the error that occurs during learning. GUI development applied to the prototype shows the target pH concentration (3.8 or less) and the number of cells (10⁸ or more) of complex microorganisms in an order suitable for culturing according to the water temperature selected by the user. In order to evaluate the performance of the proposed microbial incubator, the results of experiments conducted by authorized testing institutes showed that the average pH was 3.7 and the number of cells of complex microorganisms was 1.7 × 10⁸. Therefore, the effectiveness of the deep learning structure for the complex microbial incubator applying the deep learning prediction result information proposed in this paper was proven.