• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.639-650
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• 2022

Abeliophyllum distichum Nakai, a rare plant with distylous characteristics, is native to certain parts of the Korean Peninsula. It is registered on the IUCN Red List of Threatened Species as a globally endangered plant. This study was conducted to establish an appropriate local conservation management plan suitable for future A. distichum populations by comparing and analyzing the flowering characteristics and population size according to distyly based on the results of quantitative surveys in 14 regions, including 8 areas with native populations of A. distichum and 6 natural monument populations. The number of individuals appearing in each population group was surveyed, and the flowering individuals were identified by style as being either pin or thrum flower types as they were being examined and recorded on the site. In total, 13,130 individuals of A. distichum (7,003 flowering and 6,127 non-flowering individuals) were recorded, but the balance of the number of pin- and thrum-flowered individuals in each population was not significant (p<0.05), indicating an imbalanced state. In particular, the Yeongdong (YD) population was very disproportionate compared to other populations, suggesting that its genetic diversity was low and the possibility of inbreeding was high. The average flowering and fruiting rates by management unit were much higher in the natural monument populations (89.2% and 55.3%, respectively) than in the natural habitat populations (39.0% and 8.5%, respectively). It may be due to a difference in reproductive growth resulting from light inflow into the forest caused by the upper crown closure. The area of occupation (AOO) of A. distichum on the Korean Peninsula covered an area of 23,224.5 m². Although the natural monument population was smaller than the natural habitat population, its density was higher, likely as a result of the periodic management of natural monument populations, where the installation of protective facilities in certain areas restricts population spread. Conservation of A. distichum populations requires removing the natural monument populations suspected of anthropogenic and genetic disturbances and expanding the conservation priority population by designating new protected areas. Although the habitats of natural monument populations are managed by the Cultural Heritage Administration and local governments, there are no agencies that are responsible for managing natural habitat populations. Therefore, institutional improvement in the overall management of A. distichum should be prioritized.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.329-352
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• 2022

It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.

• Journal of the Korean Orthopaedic Association
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• v.54 no.4
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• pp.309-316
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• 2019

Purpose: This study examined the residential environment and accessibility of rehabilitation for cerebral palsy (CP) to identify the problems with residential laws pertaining to the disabled and provide basic data on the health legislation for the rights of the disabled. Materials and Methods: The literature was searched using three keywords: residence, rehabilitation, and accessibility. Two items were selected: residential environment and rehabilitation accessibility. The questionnaire included 51 items; 24 were scored using a Likert scale and 27 were in the form of multiple-choice questions. Results: This study included 100 subjects, of which 93 lived at home and seven lived in a facility. Of these 93 subjects, 65% were living in apartments, usually two or more floors above ground, and 40% of them were living without elevators. According to the Gross Motor Function Classification System, subjects with I to III belonged to the ambulatory group and IV, V were in the non-ambulatory group. Subjects from both groups who lived at home found it most difficult to visit the rehabilitation center by themselves. In contrast, among those who lived at the facility, the ambulatory group found it most difficult to leave the facility alone, while the non-ambulatory group found it most difficult to use the toilet alone. Moreover, 83% of respondents thought that rehabilitation was necessary for CP. On the other hand, 33% are receiving rehabilitation services. Rehabilitation was performed for an average of 3.6 sessions per week, 39 minutes per session. Conclusion: There is no law that ensures secure and convenient access of CP to higher levels. Laws on access routes to enter rooms are insufficient. The disabled people's law and the disabled person's health law will be implemented in December 2017. It is necessary to enact laws that actually reflect the difficulties of people with disabilities. Based on the results of this study, an investigation of the housing and rehabilitation of patients with CP through a large-scale questionnaire will necessary.

• Korea Trade Review
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• v.42 no.5
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• pp.137-159
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• 2017

This study divides manufacturing in 18 countries including Korea, China, Japan and OECD countries into 11 areas and estimates and compares the technological efficiency of each industry. The traditional view of productivity is to increase production capacity through technological innovation or process innovation, but it is also influenced by the technological efficiency of production process. A Stochastic Frontier Production Model (SFM) is a representative method for estimating the technical efficiency of such production. First, as a result of estimating the production function by setting the output variable as total output or value-added, in both cases, the output increased significantly in all manufacturing sectors as inputs of labor, capital, and intermediate increased. On the other hand, R&D investment has a large impact on output in chemical, electronics, and machinery industries. Next, as a result of estimating the technological efficiency through the production function, when the total output is set as the output variable, the overall average of each sector is 0.8 or more, showing mostly high efficiency. However, when value-added was set, Japan had the highest level in most manufacturing sectors, while other countries were lower than the efficiency of the total output. Comparing the three countries of Korea, China and Japan, Japan showed the highest efficiency in most manufacturing sectors, and Korea was about half or one third of Japan and China was lower than Korea. However, in the food and electronics sectors, China is higher than Korea, indicating that China's production efficiency has greatly improved. As such, Korea is not able to narrow its gap with Japan relatively faster than China's rapid growth. Therefore, various policy supports are needed to promote technology development. In addition, in order to improve manufacturing productivity, it is necessary to shift to an economic structure that can raise technological efficiency as well as technology development.

• Korean Journal of Ecology and Environment
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• v.55 no.1
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• pp.84-98
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• 2022

Estuary is important in terms of biodiversity because it has the characteristics of transition waters, created by the mixing of fresh- and seawater. The estuarine water circulation provides a variety of habitats with different environments by inducing gradients in the chemical and physical environment, such as water quality and river bed structure, which are ultimately the main factors influencing biological community composition. If the water circulation is interrupted, the loss of brackish areas and the interception of migration of biological communities will lead to changes in the spatial distribution of biodiversity. In this study, among the sites covered by the Estuary Aquatic Ecosystem Health Assessment, we selected study sites where changes in biodiversity can be assessed by spatial gradient from the upper reaches of the river to the lower estuarine area. The α-, γ- and β-diversity of diatom, benthic macroinvertebrates, and fish communities were calculated, and they were divided into open and closed estuary data and compared to determine the trends in biodiversity variation due to estuarine circulation. As results, all communities showed higher γ-diversity at open estuary sites. The benthic macroinvertebrate community showed a clear difference between open and closed estuaries in β-diversity, consequently the estuarine transects were considered as a factor that decreases spatial heterogeneity of their diversity among sites. The biodiversity trends analyzed in this study will be used to identify estuaries with low γ- and β-diversity by community, providing a useful resource for further mornitoring and management to maintain estuarine health.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.134-141
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• 2023

Objectives : The purpose of this study was investigating the differences in temperament, personality, and cognitive function among athletes and non-athletes, as well as differences within athlete groups participating in different-paced sports like baseball and basketball. Methods : A total of 57 professional basketball players, 51 professional baseball players, and 44 non-athletes subjected to temperament and characteristics inventory assessments and computerized neurocognitive function test. One-way analysis of variance (ANOVA) was employed to analyze the average differences in demographic characteristics, temperament, personality traits, and cognitive functions among the three groups, followed by Bonferroni post hoc tests. Comparisons between starters and non-starters within the athlete groups were conducted using the Mann-Whitney U test. Results : In the analysis of temperament, the basketball and baseball player groups exhibited higher reward dependence and persistence compared to the control group. Additionally, in the assessment of personality traits, both basketball and baseball player groups scored higher in self-directedness and cooperativeness compared to the control group, whereas self-transcendence scores were lower. In cognitive ability assessments, baseball and basketball players outperformed the control group in emotional perception tests. Both baseball and basketball players showed lower card movement counts compared to the control group. Conclusions : This study compared the differences in temperament, personality, and cognitive abilities between professional basketball and baseball players and non-athletes. These results provide valuable insights into the temperament, personality, and cognitive abilities of professional athletes, contributing important information for athlete development and coaching goals in the future.

• Korean Journal of Culture and Social Issue
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• v.12 no.1
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• pp.129-160
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• 2006

The purposes of this study were to find 1) the realities of social anxiety and perception of various kinds of social problems that exists in Korean society as well as the perception on the events that causes the social anxiety, 2) to see the difference of perceived level of social anxiety through variables of social demography and difference of perception on Korean society. The sample was distributed according to population size distinguishing the nation to 6 regions. The data of 1,375 adult respondents were analysed. The results are as follows. First of all, respondents mentioned that the most immediate problem to be solved in Korean society was financial anxiety, and the most desirable state of society was when the society is financially stabled. Single question was measured about social anxiety of Korean society and scored 6.84 from full marks of 10, showing difference in variables for instance sex, age, and subjective S.E.S. where women, aged under 20, and perceived low class group showed the highest rate of social anxiety. However, there weren't any difference found in social anxiety of the variables like presence of religion, educational background, residence, and monthly average household income. Also, there were differences in level of social anxiety according to the difference of perception of Korean society. Higher the perceived unpredictability, uncontrollability, and unmovability to the upper class, unfairness, and uncertainty, unreliability of the Korean society, higher the social anxiety. And the lower the perceived chance of success of reformation, higher the social anxiety. It was also found that the perceived social anxiety is influenced by social accidents and phenomenon as unemployment, economic depression, and the gap between rich and poor as well as the increase of crime through effluence of personal information. Finally the limitations and implications of this study were discussed.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.339-350
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• 2024

Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.