• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.72-84
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• 2023

The Rural Revitalization Strategy (2018-2022), published by the Chinese State Council in 2018, represents a new period of rural development in China. Suburban areas are more convenient than other rural areas in integrated urban-rural development but are under greater pressure from construction and industrial pollution. As a rural area with a high proportion of rural areas, it would be valuable for Henan province to gain a comprehensive grasp of rural human settlementst while identifying problems and proposing solutions. The purpose of this study is to analyze the satisfaction of the evaluation items based on the usage status and life perception of the residents of Tai Nan village, a suburb-type rural village in Henan province. The study proposes improvement programs based on the evaluation results. As a result of the study, 24 evaluation items were derived and divided into five categories: "Living Service Facilities", "Housing Environment, "Road Environment", "Health & Ecology Environment", and "Social & Cultural Environment". The Fuzzy Comprehensive Evaluation Method was used to find the overall satisfaction level of the human living environment in Tai Nan village, which was "average", among which "Living Service Facilities" was the most important "Health & Ecology Environment" was the least satisfied. Based on these results, an improvement plan is proposed in three stages. First, the living service will be improved while strengthening the facility management of the hygiene and the ecological environment. Second, reasonable improvement of housing and the road environment will be applied. Third, programs will be introduced to cultivate residents' ability to build their own and improve the social and cultural environment. This study provides basic data for the future improvement of rural settlements in the suburban areas of Henan province and is of great significance in gradually improving the the residents' quality of life.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.1
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• pp.35-46
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• 2023

This study investigated and analyzed ancient records on the type, planting background, and construction process of Gwanbang forest(關防林) planned for military defense during the Joseon Dynasty to find out the purpose, location, and planting species of Gwanbang forest. The research results were as follows. During the Joseon Dynasty, Gwanbang forests were created around various government facilities(關防施設), such as Eupseong(邑城), major government offices, camps, and fortifications, for the purpose of defending against enemies. Gwanbang forest includes Yeongaeglim(嶺阨林), which was created on the crest of a strategically important hill, and Military Forest created for military purposes. Most of the spirit forest was designated as Geumsan(禁山) and protected and managed, and the Gwanbang forest was created for various purposes such as shielding, flood damage and river bank erosion prevention as well as external defense. In addition, in order to continuously and efficiently produce wood, which is a material for ships, buildings, and agricultural tools, in most cases, large areas were created as mixed forests. As for the species constituting the Gwanbang forest, there are records of tangerine tree, which is effective for defense because it has thorns, and deciduous broad-leaved trees such as zelkova, elm, willow, david hemiptelea, and oak appear. In the case of Ganghwa island, which served as the defense of the capital and the royal family during the Joseon Dynasty, several records have confirmed that a forest densely planted with trifoliate orange was created for the purpose of Gwanbang forest to reinforce the defense of the outer fortress. Based on historical research in the literature, assuming that the natural monument 'Gapgotri tangerine tree in Ganghwa Island' was planted in the 30th year of King Sukjong(1704), the first record of planting trifoliate orange in Ganghwa Island, the maximum age is estimated to be more than 319 years.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.2
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• pp.147-166
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• 2023

This study aimed to develop and apply guidelines for calculating greenhouse gas emissions to activate the contribution of the Korea Institute of Geoscience and Mineral Resources (KIGAM) for institutional-level research activities. In addition, we intended to improve awareness by identifying greenhouse gas emissions from KIGAM's basic research and development (R&D) activities in fiscal 2022. Herein, the research plan and budget contents of individual projects were analyzed, whilst the boundaries and scopes of greenhouse gas emissions were determined, with 22 cases being derived as either direct, indirect, or other sources of emissions. Subsequently, research activity emissions were calculated by emission source. The greenhouse gas emissions of KIGAM's 2022 basic project R&D activities were 2,041.506 tCO2eq, of which direct emissions were 793.235 tCO2eq (38.86%), indirect emissions comprised 305.647 tCO2eq (14.97%), whilst other emissions were 942.624 tCO2eq (46.18%). In particular, greenhouse gas emissions per 100 million won in the KIGAM's basic projects for fiscal 2022 (a total of 96.661 billion won) was calculated as 2.11 tCO2eq, whilst greenhouse gas emissions per participating researcher (was 4.800 tCO2eq. Such calculations should be carried out annually rather than once and accumulated for at least 5 years. Accordingly, it will be possible to standardize specific matters that influence emissions according to differences in research field characteristics and methods, thus guiding greenhouse gas emission reduction management in the future and evaluating the contributions of Environmental, Social and Governance (ESG) management to the environmental sector.

• Korean Journal of Environment and Ecology
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• v.37 no.3
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• pp.209-220
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• 2023

Over the past few centuries, widespread changes to natural ecosystems caused by human activities have severely threatened biodiversity worldwide. Understanding changes in ecosystems is essential to identifying and managing threats to biodiversity. In line with this need, the IUCN Council formed the IUCN Global Ecosystem Typology (GET) in 2019, taking into account the functions and types of ecosystems. The IUCN provides maps of 10 ecosystem groups and 108 ecological functional groups (EFGs) on a global scale. According to the type classification of IUCN GET ecosystems, Korea's ecosystem is classified into 8 types of Realm (level 1), 18 types of Biome (level 2), and 41 types of Group (level 3). GETs provided by IUCN have low resolution and often do not match the actual land status because it was produced globally. This study aimed to increase the accuracy of Korean IUCN GET type classification by using land cover maps and producing maps that reflected the actual situation. To this end, we ① reviewed the Korean GET data system provided by IUCN GET and ② compared and analyzed it with the current situation in Korea. We evaluated the limitations and usability of the GET through the process and then ③ classified Korea's new Get type reflecting the current situation in Korea by using the national data as much as possible. This study classified Korean GETs into 25 types by using land cover maps and existing national data (Territorial realm: 9, Freshwater: 9, Marine-territorial: 5, Terrestrial-freshwater: 1, and Marine-freshwater-territorial: 1). Compared to the existing map, "F3.2 Constructed lacustrine wetlands", "F3.3 Rice paddies", "F3.4 Freshwater aquafarms", and "T7.3 Plantations" showed the largest area reduction in the modified Korean GET. The area of "T2.2 Temperate Forests" showed the largest area increase, and the "MFT1.3 Coastal saltmarshes and reedbeds" and "F2.2 Small permanent freshwater lakes" types also showed an increase in GET area after modification. Through this process, the existing map, in which the sum of all EFGs in the existing GET accounted for 8.33 times the national area, was modified so that the total sum becomes 1.22 times the national area using the land cover map. This study confirmed that the existing EFG, which had small differences by type and low accuracy, was improved and corrected. This study is significant in that it produced a GET map of Korea that met the GET standard using data reflecting the field conditions. 

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.31-39
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• 2023

The purpose of this study is to propose a scientific performance evaluation framework for measuring and managing the overall outcome of complex types of projects that are linked to public demand-based commercialization, such as information system projects and public procurement, in integrated national R&D projects. In the case of integrated national R&D projects that involve multiple research institutes to form a single final product, and in the case of demand-based demonstration and commercialization of the project results, the existing evaluation system that evaluates performance based on the short-term outputs of the detailed tasks comprising the R&D project has limitations in evaluating the mid- and long-term effects and practicality of the integrated research products. (Moreover, as the paradigm of national R&D projects is changing to a mission-oriented one that emphasizes efficiency, there is a need to change the performance evaluation of national R&D projects to focus on the effectiveness and practicality of the results.) In this study, we propose a performance evaluation framework from a structural perspective to evaluate the completeness of each national R&D project from a practical perspective, such as its effectiveness, beyond simple short-term output, by utilizing the Hourglass model. In particular, it presents an integrated performance evaluation framework that links the top-down and bottom-up approaches leading to Tool-System-Service-Effect according to the structure of R&D projects. By applying the proposed detailed evaluation indicators and performance evaluation frame to actual national R&D projects, the validity of the indicators and the effectiveness of the proposed performance evaluation frame were verified, and these results are expected to provide academic, policy, and industrial implications for the performance evaluation system of national R&D projects that emphasize efficiency in the future.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.869-881
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• 2023

Purpose: This study aims to come up with improvement measures to improve the effectiveness of child safety measures. Method: The current status of child safety accidents was investigated and implications were deduced by analyzing major child safety measures by government department in the past. In addition, a perception survey was conducted on 1,000 people including children, guardians, and children's facility workers who are subject to child safety policies. Result: Regarding the safety of children's living space(environment), 35.3% of guardians answered that more than 1/3 of them were not safe. Both guardians(95.3%) and children's facility workers(89%) answered that there was the highest risk of 'traffic accidents', and the second risk factor was parents(carelessness of workers at children's facilities) and children's facility workers(careless of guardians at home). Looking at the risks by place, "road and sidewalk" was the most dangerous place and for child safety, guardians(64.3%) and workers (78.3%) both said that the role of "parent" is the most important. For improvements to prevent child safety accidents, the response rate of "strengthening safety management of road traffic facilities" is the most necessary with 75.8% for guardians and 65% for child use facilities. Conclusion: The reinforcement measures to strengthen the effectiveness of child safety measures are as follows. First, in order to ensure the continuity of child safety measures, it should be operated effectively so that those subject to the establishment of the Comprehensive Plan for Child Safety, which took effect in August 2022, can feel it. Second, in order to improve the sensitivity of children's policy targets, promotion measures that take into account the characteristics of each child safety field should be continuously strengthened. Third, it is necessary to expand safety infrastructure for each field to secure child safety. Fourth, it is necessary to strengthen safety education that can ensure safety for children themselves and to come up with detailed measures to make safety education for parents(guardians) mandatory.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.1
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• pp.107-124
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• 2023

As getting in 4th Industrial Revolution Times, Continuing Education Enrolled Students(CEES) trying to find loophole for jepordized current life and need job transfer have surged their interest significantly on starting new business to bring up their post career after retirement through self-improvement. Government and university have actively initiated diverse policies of promoting startup for CEES in kicking off entrepreneurship courses and programs. However, relevant main policy, 'The 2nd University Startup Education Five-Year Plan (draft)' have too chiefly focused on theoretical start-up education rather than practical courses, causing the problem of inappropriate support for implementing real startup and business (Ministry of Education, 2018). This study is brought to empirically investigate the effect of self-efficacy as perspective of the impact of entrepreneurship education on entrepreneurial intention and behavior to come up with problem of poor entrepreneurial environment and entrepreneurship education to CEES. As to empirical research, this paper deliver on-line survey to CEES from September to October 2022, collect 207 effective feedbacks, In order to verify the reliability of the scale, the Cronbach's Alpha Coefficient (Cronbach's α) was calculated, analyzed, and measured. For hypothesis test, this paper utilize the multiple regression analysis statistical analysis method and use the SPSS 22.0 statistical processing program. Empirical results show, first, it was found that self-efficacy had a significant effect on start-up education. Second, start-up education had a significant effect on the intention to start a business of adult learners. Third, start-up education had a significant effect on the start-up behavior of adult learners. Fourth, self-efficacy had a significant effect on the intention of adult learners to start a business. Fifth, self-efficacy had a significant effect on the start-up behavior of adult learners. Sixth, self-efficacy had a mediating effect in the relationship between entrepreneurship education and adult learners' intention to start a business. Seventh, self-efficacy had a complete mediating effect in the relationship between start-up education and adult learners' start-up behavior. This paper is brought three significant implications. First, main consideration developing entrepreneurship education tools for CEES need to falls on defining potential needs of CEES as segmenting as to coming up with diversity of CEES's characteristics such as gender, age, experience, education, and occupation. Second, as to design specific entrepreneurship education program, both practical training program of utilizing CEES's career field experience benchmarking best practice startup and venture cases from domestic and global, and professional startup program of CEES initiating directly startup from ideation to develop business plan with pitching and discussing. Third, entrepreneurship education for CEES should be designed to incubate self-efficacy to enhance entrepreneurial intention of implementing entrepreneurial behavior as a real, eventually leading solid support system of self-improvement for CEES' Retirement life planning.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.