• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.1
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• pp.23-35
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• 2007

Nowadays, as a result of increasing income and spare time, the social demands for better living environment become more increasing. Above all, landscape improvement, the essential part of physical environment, will be a more important subject in urban planning. In these circumstances, classification of urban scenic quality is required for urban landscape development programs. The major purpose of this study is to suggest a technical method of designing urban scenic quality map for urban district area based on the scenery management system of the USDA forest service and literature studies. As a conclusion of this study, four steps are desirable for the technical method for designing a scenic quality map of urban districts areas : 1) Define a landscape unit on the map, 2) Take a photograph of these landscape unit on site, 3) Evaluate the landscape unit by semantic differential scale with landscape adjectives, and 4) Draw the scenic quality map, investigate the landscape characteristics and suggest the landscape scenic development plans.

• Journal of Forest and Environmental Science
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• v.19 no.1
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• pp.85-98
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• 2003

The articles, published in the Journal of Korean Forestry from Number 1(1962) to Number 6, Volume 91(2002), were surveyed and investigated for the research trend analysis about resource-plants for special use or purpose, i. e., edible plants, medicinal plants, feed resource, landscape plants, fiber plants, industrial usuage, and bee plants. If the purpose or subject matter of the research was construction or furniture timber production, mushrooms and/or pulp and paper, such research was not included in this study. These articles were classified again depending on the content of research into 14 categories: habitat environment, ecology, physiology, propagation, silviculture (tending and culture), genetics and breeding, identification, insect and disease control, animal-related research, component analysis, vegetation survey, biotechnology, management, and review. Among the total 1.434 articles published, 396 ones (27.6%) were related with plants for special use or purpose. Vegetation survey was 60 (15.2%): physiology 56(14.1%) : genetics and breeding 56(14.1%): propagation 53(13.4%): and ecology 37(9.3%). Siviculture research field included 11 articles (2.8%), which indicates that the management of resource-plants is so far from economic income as seen in the low number of management research filed articles, i. e., only 6 reports (1.5%) Korean white pine was most popular for research and included 42 articles: Robinia pseudoacacia 23: Castanea crenata 14: and ginkgo tree 14. Research related with these species had focused mainly on propagation, physiology, genetics and breeding, ecology and pest control. Based on this survey and analysis, the followings are suggested: 1. More research is required on forest herbaceous plants. 2. Cooperative research work with other industrial and/or scientific area is recommendable for commercialization including medicine, cosmetics, and food etc. 3. Research on resource-plant conservation, which includes biology, social education and policy, should be supported for next generation. 4. Mutual correspondence and information exchange about the research results between researchers and institutes is more necessary than now.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.42-51
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• 2020

This study was performed to support the 6th forest basic planning by Korea Forest Service as predicting the change of forestland area by the transition of land use type in the future over 35 years in South Korea. It is very important to analyze upcoming forestland area change for future forest planning because forestland plays a basic role to predict forest resources change for afforestation, production and management in the future. Therefore, the transitional interaction between land use types in future of South Korea was predicted in this study using econometrical models based on past trend data of land use type and related variables. The econometrical model based on maximum discounted profits theory for land use type determination was used to estimate total quantitative change by forestland, agricultural land and urban area at national scale using explanatory variables such as forestry value added, agricultural income and population during over 46 years. In result, it was analyzed that forestland area would decrease continuously at approximately 29,000 ha by 2027 while urban area increases in South Korea. However, it was predicted that the forestland area would be started to increase gradually at 170,000 ha by 2050 because urban area was reduced according to population decrement from 2032 in South Korea. We could find out that the increment of forestland would be attributed to social problems such as urban hollowing and localities extinction phenomenon by steep decrement of population from 2032. The decrement and increment of forestland by unbalanced population immigration to major cities and migration to localities might cause many social and economic problems against national sustainable development, so that future strategies and policies for forestland should be established considering such future change trends of land use type for balanced development and reasonable forestland use and conservation.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.3
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• pp.11-24
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• 2024

Purpose : This study aims to identify the factors influencing health-related quality of life through machine learning of the general characteristics of patients with hypertension and to provide a basis for related research on patients, such as intervention strategies and management guidelines in the field of physical therapy for health promotion. Methods : Annual data from the second Korean Health Panel (Version 2.0) from 2019 to 2020, conducted jointly by the Korea Health and Social Research Institute and the National Health Insurance Service, were analyzed (Korea Health Panel, 2024). The data used in this study was collected from January to July 2020, and the data was collected using computer-assisted face-to-face interviews. Of the 13,530 household members surveyed, 1,368 were selected as the final study participants after removing missing values from 3,448 individuals diagnosed with hypertension by a doctor. Results : The results showed that walking (P2) was the most significant factor affecting health-related quality of life in random forest, followed by perceived stress (HS1), body mass index (BMIc), total household income (TOTc), subjective health status (SRHc), marital status (Marr), and education level (Edu). Conclusion :To prevent and manage chronic diseases such as hypertension, as well as to provide customized interventions for patients in advanced stages of the disease, research should be conducted in the field of physical therapy to identify influencing factors using machine learning. Based on the findings of this study, we believe that there is a need for additional content that can be utilized in the field of physical therapy to improve the health-related quality of life of patients with hypertension, such as diagnostic assessment and intervention management guidelines for hypertension, and education on perceived stress and subjective health status.

• Journal of Forest and Environmental Science
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• v.29 no.1
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• pp.71-80
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• 2013

Present study analyzes the rooftop gardening status, floristic composition and cost and return of the rooftop garden in Sylhet City Corporation of northeastern Bangladesh. Data was collected from 450 rooftop gardeners randomly during July-September 2010. Study reveal that rooftop gardening is generally for mental satisfaction (95.3%) followed by leisure time activity (87.8%) in the study area and almost all the family members of gardeners' were involved; while collection of planting materials, sites preparation and marketing of products were reported to be carried out by males only (male 71.33%). Middle income classes were most interested in rooftop gardening (43.78%). The survey recorded 53 plant species (35 families) of which Cucurbitaceae family represented highest eight species. Shrubs (28%) were highest followed by herbs (26%) among agri-crops (36%) and flower species (30%). About 89% of the rooftop gardeners procured planting materials from nursery, market, fair, neighbor, relative and friends and they mostly prefer to use seedlings (48%) for roof gardening followed by direct seed sowing (21%). Gardeners sell products sporadically in different local markets, directly or through intermediaries, with no uniform pricing for system. Rooftop gardening improves the food security and meet nutritional deficiency to the gardeners. Survey revealed that generally very few people consider rooftop gardening commercially to get profit and from the cost-return analysis this gardening system can be economically viable if proper and scientifically managed. The study conclude that active government and NGOs could play vital role to increasing this activities by providing training and motivate people with technical aspects of rooftop gardening.

• Korean Journal of Environmental Agriculture
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• v.31 no.2
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• pp.129-136
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• 2012

BACKGROUND: The changes in the climatic conditions have brought potentially significant new challenges, most critical are likely to be its impact on local livelihoods, agriculture, biodiversity and environments. Water induced disasters such as landslides, floods, erratic rain etc., are very common in developing countries which lead to changes in biological, geophysical and socioeconomic elements. The extent of damages caused by natural disasters is more sever in least developing countries. However, disasters affect women and men differently. In most of the cases women have to carry more burden as compared to their male counterpart during the period of disasters. METHODS AND RESULTS: This study examines the impact of disasters on the local livelihood especially agriculture and income generating activities of women in three districts of Nepal. The study uses the primary data collected following an exploratory approach, based on an intensive field study. The general findings of the study revealed that women had to experience hard time as compared to their male counterpart both during and after the disaster happen. Women are responsible for caring their children, collecting firewood, fetching water, collecting grass for livestock and performing household chores. Whereas, men are mainly involved in out-migration and remained out-side home most of the time. After the disaster occurred, most of the women had to struggle to support their lives as well as had to work longer hours than men during reconstruction period. Nepal follows patriarchal system and men can afford more leisure time as compared to women. During the disaster period, some of the households lost their agricultural lands, livestock and other properties. These losses created some additional workload to women respondent, however at the same time; they learn to build confidence, self-respect, self-esteem, and self-dependency.Although Nepal is predominantly agriculture, majority of the farmers are at subsistence level. In addition, men and women have different roles which differ with the variation in agro-production systems. Moreover women are extensively involved in agricultural activities though their importances were not recognized. Denial of land ownership and denial of access to resources as well as migration of male counterparts are some of the major reasons for affecting the agricultural environments for women in Nepal. CONCLUSION: The shelter reconstruction program has definitely brought positive change in women's access to decision making. The gradual increase in number of women respondent in access to decision making in different areas is a positive change and this has also provided them with a unique opportunity to change their gendered status in society.Furthermore, the exodus out-flow of male counterparts accelerated the additional burden and workload on women.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.751-761
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• 2019

Mt. Baekdu, Mt. Aso, Mt. Sakurajima, Mt. Kikai and etc are distributed around the Korean Peninsula. Recently signs of eruption of Mt. Baekdu are increasing, raising concerns over possible damage to volcanic ash from seasonal winds during the winter eruption. Therefore, detailed procedures for investigation and countermeasures for volcanic ash spread and damage are required. But the standards for the warning and alarm signal of volcanic ash presented by Korea Ministry of Government Legislation are vague, with "when damage is expected" and "when serious damage is expected". In this study, to analyze the damage threshold and to apply the cases of overseas damage to the country, a survey was conducted on the establishment of domestic spatial information by public institutions with public confidence. As a result of the investigation of damage from volcanic ash overseas, the details of the damage cases were different depending on the type of life or income sources of each country. Therefore, instead of applying the volcanic ash damage cases abroad in Korea, spatial information analysis was performed to reflect domestic social and natural characteristics. In addition, we selected the areas to be considered in the event of volcanic ash damage in Korea. Finally, domestic volcanic ash damages should be classified as health, residential, road, railroad, aviation, power, water, agriculture, livestock, forest, and soil. When establishing the volcanic ash alarm optimized for Korea in the future, overseas volcanic ash damage cases and domestic spatial information construction in this study will be helpful in policy establishment.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.49-56
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• 2019

Urban green spaces have been contributing to the improvement of environmental, mental, and physical health for humans. In addition, recent studies showed the potential role of vegetation in reducing the amount of crime in inner-city neighborhoods at the micro-scale level. However, little is known about the positive role of urban green areas in improving urban safety at the regional level. The purpose of this study is to examine the relationship between urban green areas and actual outdoor crime rates, while also considering socio-demographic factors. The study area is the city of Austin, Texas, USA, which consists of 506 block groups. This study utilized socio-demographic factors based on U.S. Census data and vegetation-related factors utilizing GIS and ENVI software. For analyses, the analysis of variance (ANOVA) and an ordinary least square (OLS) regression were utilized. The results from ANOVA showed that yearly crime rates per acre for areas having 0%~25% trees in their neighborhoods were 0.46% and 1.05% higher than those of having 25%~50% and >50% trees in the neighborhoods, respectively. The results from the OLS regression represented that income, NDVI and park rates in neighborhoods were negatively associated with the crime rate per acre, whereas the percentage of minorities and the percentage of teenage school dropouts were positively associated with the crime rate per acre. This study implies that urban green areas may help to improve the safety of urban areas.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.1-16
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• 2007

The use of information on natural resources is indispensable to most agricultural activities to avoid disasters, to improve input efficiency, and to increase lam income. Most information is prepared and managed at a spatial scale called the "Hydrologic Unit" (HU), which means watershed or small river basin, because virtually every environmental problem can be handled best within a single HU. South Korea consists of 840 such watersheds and, while other watershed-specific information is routinely managed by government organizations, there are none responsible for agricultural weather and climate. A joint research team of Kyung Hee University and the Agriculture, forestry and Fisheries Information Service has begun a 4-year project funded by the Ministry of Agriculture and forestry to establish a watershed-specific agricultural weather information service based on "high definition" digital climate maps (HD-DCMs) utilizing the state of the art geospatial climatological technology. For example, a daily minimum temperature model simulating the thermodynamic nature of cold air with the aid of raster GIS and microwave temperature profiling will quantify effects of cold air drainage on local temperature. By using these techniques and 30-year (1971-2000) synoptic observations, gridded climate data including temperature, solar irradiance, and precipitation will be prepared for each watershed at a 30m spacing. Together with the climatological normals, there will be 3-hourly near-real time meterological mapping using the Korea Meteorological Administration's digital forecasting products which are prepared at a 5 km by 5 km resolution. Resulting HD-DCM database and operational technology will be transferred to local governments, and they will be responsible for routine operations and applications in their region. This paper describes the project in detail and demonstrates some of the interim results.