• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.24-36
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• 2021

Countries around the world, including the Republic of Korea, are participating in efforts to preserve biodiversity. Concerning species, in particular, studies that aim to find potential habitats and establish conservation plans by conducting habitat suitability analysis for specific species are actively ongoing. However, few studies on mid- to long-term changes in suitable habitat areas are based on accumulated information. Therefore, this study aimed to analyze the time-series changes in the habitat suitable area and examine the otters' changing pattern (Lutra lutra) designated as Level 1 endangered wildlife in Gangwon-do. The time-series change analysis used the data on otter species' presence points from the 2nd, 3rd, and 4th national natural environment surveys conducted for about 20 years. Moreover, it utilized the land cover map consistent with the survey period to create environmental variables to reflect each survey period's habitat environment. The suitable habitat area analysis used the MaxEnt model that can run based only on the species presence information, and it has been proven to be reliable by previous studies. The study derived the habitat suitability map for otters in each survey period, and it showed a tendency that habitats were distributed around rivers. Comparing the response curves of the environmental variables derived from the modeling identified the characteristics of the habitat favored by otters. The examination of habitats' change by survey period showed that the habitats based on the 2nd National Natural Environment Survey had the widest distribution. The habitats of the 3rd and 4th surveys showed a tendency of decrease in area. Moreover, the study aggregated the analysis results of the three survey periods and analyzed and categorized the habitat's changing pattern. The type of change proposed different conservation plans, such as field surveys, monitoring, protected area establishment, and restoration plan. This study is significant because it produced a comprehensive analysis map that showed the time-series changes of the location and area of the otter habitat and proposed a conservation plan that is necessary according to the type of habitat change by region. We believe that the method proposed in this study and its results can be used as reference data for establishing a habitat conservation and management plan in the future.

• Journal of Nutrition and Health
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• v.54 no.2
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• pp.179-198
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• 2021

Purpose: This study examined general characteristics, health status, accessibility to medical services, health-related quality of life, dietary behavior, and energy and nutrient intakes of the elderly at different levels of food security utilizing data from the 7th Korea National Health and Nutrition Examination Survey (2016-2018). Methods: The elderly subjects (1,721 males and 2,271 females) were divided into 3 groups (secure, mildly insecure, moderately/severely insecure) according to their food security levels. Health and nutrient status was determined using energy intake, nutrient density, the prevalence of insufficient nutrient intake, dietary behavior, and health status. Results: The elderly with food insecurities had a lower self-evaluated health status and a higher prevalence of physician-diagnosed chronic diseases such as arthritis, osteoarthritis, rheumatoid arthritis, osteoporosis for males, and hypertension, stroke, arthritis, and osteoarthritis for females. The associated financial burden was the major reason for not accessing medical services in the food insecure group. Furthermore, the food insecure group had a higher risk of impaired health-related quality of life compared to the secure group. The proportion of subjects with an energy intake below the estimated energy requirement was higher in the food insecure group and a significantly higher prevalence of insufficient intake was observed for all the nutrients (proteins, vitamin A, vitamin B₁, vitamin B₂, niacin, vitamin C, calcium, and iron) assessed in this study compared to the food secure group. Conclusion: This study suggests that food insecurity poses a challenge to the health and nutritional status of the elderly population in Korea and needs proper management. It would be helpful to develop food and nutrition assistance programs to ensure the food stability of the elderly population and assure quality to address gaps in their nutrient intake.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.147-157
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• 2022

This study tried to propose a smart farm technology strategy suitable for the domestic situation, focusing on the differentiation suitable for the domestic situation of ICT technology. In the case of advanced countries in the overseas agricultural industry, it was confirmed that they focused on the development of a specific stage that reflected the geographical characteristics of each country, the characteristics of the agricultural industry, and the characteristics of the people's demand. Confirmed that no enemy development is being performed. Therefore, in response to problems such as a rapid decrease in the domestic rural population, aging population, loss of agricultural price competitiveness, increase in fallow land, and decrease in use rate of arable land, this study aims to develop smart farm ICT technology in the future to create quality agricultural products and have price competitiveness. It was suggested that the smart farm should be promoted by paying attention to the excellent performance, ease of use due to the aging of the labor force, and economic feasibility suitable for a small business scale. First, in terms of economic feasibility, the ICT technology is configured by selecting only the functions necessary for the small farm household (primary) business environment, and the smooth communication system with these is applied to the ICT technology to gradually update the functions required by the actual farmhouse. suggested that it may contribute to the reduction. Second, in terms of performance, it is suggested that the operation accuracy can be increased if attention is paid to improving the communication function of ICT, such as adjusting the difficulty of big data suitable for the aging population in Korea, using a language suitable for them, and setting an algorithm that reflects their prediction tendencies. Third, the level of ease of use. Smart farms based on ICT technology for the development of the Industry6.0 (1.0(Agriculture, Forestry) + 2.0(Agricultural and Water & Water Processing) + 3.0 (Service, Rural Experience, SCM)) perform operations according to specific commands, finally suggested that ease of use can be promoted by presetting and standardizing devices based on big data configuration customized for each regional environment.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• Korean Journal of Environment and Ecology
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• v.36 no.2
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• pp.118-138
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• 2022

This study was conducted to identify the vegetation structure of major vegetation by region and elevation in the subalpine zone of Seoraksan National Park and prepare an inventory of flora. We reviewed the results of the previous subalpine studies and, through a preliminary survey, determined that the first appearance point of subalpine vegetation was about 800 m based on the south. Then we conducted a site survey by installing a total of 77 plots, including 12 plots on the northern Baekdamsa-Madeungnyeong trail (BD), 13 plots on the west Hangyeryeong-Kkeutcheong trail (HG), 13 plots on the east side of Sinheungsa-Socheongbong trail (SA), and 39 plots in the southern Osaek-Kkeutcheong, Osaek-Daecheongbong trail (OS), in an interval of 50 m above sea level. The analysis classified 7 communities, including Qercus mongolica-Abies holophylla-Acer pseudosieboldianumcommunity, Q. mongolica-Tilia amurensiscommunity, Q. mongolica-Pinus koraiensiscommunity, Q. mongolica-A. pseudosieboldianumcommunity, Betula ermanii-A. nephrolepiscommunity, P. koraiensis-A. nephrolepiscommunity, and mixed deciduous broad-leaf tree community according to the species composition based on the appearance of the major subalpine plants such as Quercus mongolica, Betula ermanii, and Abies nephrolepis, region, and elevation. 10.68±2.98 species appeared per plot (100 m²), and 110.87±63.89 individuals were identified. The species diversity analysis showed that the subalpine vegetation community of Seoraksan National Park was a mixed forest in which various species appeared as important species. Although there was a difference in the initial elevation for the appearance of major subalpine plants by region, they were distributed intensively in the elevation range of 1,100 to 1,300 m. In the Seoraksan National Park, 322 taxa, 83 families, 193 genera, 196 species, 1 subspecies, 26 varieties, and 4 forms of vascular plants were identified. One taxon of Trientalis europaeavar.arcticawas identified as the protected species. The endemic plants were 19 taxa, and 58 taxa were identified as subalpine plants.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.722-732
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• 2021

Purpose: Due to the coronavirus infection-19 (COVID) pendemics, all educational institutions were required to provide full non-face-to-face real-time education, and fire officials were required to provide fire-fighting education by applying non-face-to-face education. In this difficult situation, the National Fire Service Academy tries to find the direction of the non-face-to-face real-time education and suggest ways to improve it through a survey of the status of non-face-to-face real-time education conducted by the NFSA to fire officials. Method: A survey was conducted on fire officials under the theme of "Consciousness Survey for Improving the Quality and Specialization of Non-face-to-face Real-Time Remote Education" and an in-depth analysis was conducted based on the results. Result & Conclusion: First, professors or educational operators shall actively utilize remote education programs suitable for educational characteristics by utilizing various programs. Second, a dedicated notebook for non-face-to-face training should be provided to provide an educational environment where all learners can participate in the training without difficulty. Third, in the case of education and training that requires the use of equipment due to the nature of fire officials' education and training, it is necessary to consider it as a non-face-to-face training place by arranging educational equipment at each fire station. Fourth, it is hard to expect a satisfactory educational effect to cope with practical education with theoretical education. Therefore, facilities and programs that enable non-face-to-face real-time hands-on training should be developed. It is worth considering the proper combination of face-to-face education while maintaining the social distance as much as possible until such non-face-to-face training is possible. Fifth, non-face-to-face education is considered to have high eye fatigue due to the light and electromagnetic waves of the computer screen, and as time goes by, the concentration level decreases. Therefore, it is necessary to form an education time to reduce the eye fatigue of learners and increase concentration through proper class and rest time. Finally, professors should operate a learner participation-oriented education that allows professors and learners to interact rather than one-sided knowledge transfer education. In addition, technical problems of non-face-to-face remote education should be thoroughly prepared through preliminary system checks to ensure that education is not disrupted.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.853-865
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• 2022

In this study, from August to October 2019, we conducted a survey of the spatial distribution and dominant species of macrobenthos on the rocky intertidal zones of 38 specified islands distributed along the southern coast of Korea. On the basis of observation made using 50 × 50 cm quadrats, we identified a total of 80 species, among which, Mollusca were the most abundant fauna, with 54 species that accounted for 67.4% of the total, followed by Crustacea with 15 species (18.7%). The recorded numbers of Cnidaria, Porifera, and Echinodermata species ranged from 1 to 6. In terms of the regional patterns of species richness, specified islands in Yeosu were found to be the most species rich, supporting 61 species, whereas islands in Hadong, Namhae, and Chujado were found to have a similar level of species richness, ranging from 42 to 46 species. Islands in Boseong and Goheung were home to the fewest species, with only 29 species being recorded. At the sampling station scale, we noted a considerable difference in faunal richness, ranging from 6 (St. 6) to 33 (St. 20) species. Among the recorded species, Echinolittorina radiata was identified as the dominant species on 15 specified islands, with the next most abundant species being Tetraclita japonica, considered an indicator species of climate change, which was recorded on 11 islands. In terms of frequency, E. radiata, found on 36 islands, was identified as the most frequently occurring species, followed by Reishia clavigera (30 islands), Mytilisepta virgata (29), Nerita japonica (28), Ligia. exotica (27), and Littorina brevicula (26). Of the 80 species identified, 9, 4, and 2 species of Mollusca, Crustacea, and Cnidaria, respectively, are classified as Marine fauna of accepted foreign export, whereas 50 are Red List species, 44 are species of Least Concern, 3 are Data Deficient species, and 1 species was not evaluated. However, during the survey, we found no Near Threatened or Not Applicable species. On the basis of the findings of this survey, it would appear that the abundance and richness of macrobenthic fauna inhabiting the rocky intertidal zones of specified islands along the southern coast of Korea differ according to different habitat conditions, particularly with respect to the duration of exposure and the extent and properties of the substrata. The findings of this study will provide baseline data for future monitoring and management of specified islands in Korea.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.3
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• pp.333-344
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• 2022

The quarrying and utilization of natural building stones such as granite and marble are rapidly emerging in developing countries. A huge amount of wastes is being generated during the processing, cutting and sizing of these stones to make them useable. These wastes are disposed of in the open environment and the toxic nature of these wastes negatively affects the environment and human health. The growth trend in the world stone industry was confirmed in output for 2019, increasing more than one percent and reaching a new peak of some 155 million tons, excluding quarry discards. Per-capita stone use rose to 268 square meters per thousand persons (m²/1,000 inh), from 266 the previous year and 177 in 2001. However, we have to take into consideration that the world's gross quarrying production was about 316 million tons (100%) in 2019; about 53% of that amount, however, is regarded as quarrying waste. With regards to the stone processing stage, we have noticed that the world production has reached 91.15 million tons (29%), and consequently this means that 63.35 million tons of stone-processing scraps is produced. Therefore, we can say that, on a global level, if the quantity of material extracted in the quarry is 100%, the total percentage of waste is about 71%. This raises a substantial problem from the environmental, economical and social point of view. There are essentially three ways of dealing with inorganic waste, namely, reuse, recycling, or disposal in landfills. Reuse and recycling are the preferred waste management methods that consider environmental sustainability and the opportunity to generate important economic returns. Although there are many possible applications for stone waste, they can be summarized into three main general applications, namely, fillers for binders, ceramic formulations, and environmental applications. The use of residual sludge for substrate production seems to be highly promising: the substrate can be used for quarry rehabilitation and in the rehabilitation of industrial sites. This new product (artificial soil) could be included in the list of the materials to use in addition to topsoil for civil works, railway embankments roundabouts and stone sludge wastes could be used for the neutralization of acidic soil to increase the yield. Stone waste is also possible to find several examples of studies for the recovery of mineral residues, including the extraction of metallic elements, and mineral components, the production of construction raw materials, power generation, building materials, and gas and water treatment.