• 산림경영
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• s.75
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• pp.6-11
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• 1992

• Journal of the Korean Applied Science and Technology
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• v.35 no.1
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• pp.247-253
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• 2018

To replace the imported biomass and to effectively cope with growing RPS(Renewable Portfolio Standard) in power sector, the domestic forest biomass resources for wood pellets were estimated from the preceding research and annual growth rate of forest trees in this study. Assuming that 20% of the by-product from forest trees processing were used as raw material for wood pellet and the wood pellet production capacity was based on the average value derived from the above two methods, unused by-product and residues generated 1.99million tons in 2016, 2.28million tons in 2020 and 3.08million tons in 2030. If 20% of by-products(pebbles, sawdust, etc.) from roundwood processing were used as raw material for wood pellets, the wood pellet could be produced 2.74million tons/year in 2016, 2.95million tons/year in 2020, 3.98million tons/year in 2030. Therefore, total amounts of wood pellet would be increased to 2.74million tons/year in 2016, 3.14million tons/year in 2020, 4.23million tons/year in 2030 when it considered unused by-product and residues from wood processing as raw materials.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.215-228
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• 2018

After the housing shortage problem for the youths has invoked substantial social attention recently, Seoul's 2030 Youth Housing Program has been timely improvised and successfully providing the decent rental housing packages for the deprived youths of the City. Its housing supply rate, nevertheless, did not sufficiently catch up with the actual need of the youth group so that the program goal is seen by many to be difficult to readily achieve. In an effort to counteract such adversities, it is seen, in this study, that the clarification of the criteria that judges adjacency condition for up-zoning when a candidate housing site is adjoining to a denser land-use classes could be one effective method to augment its supply rate. This study, in this context, has performed spatial structure analyses via space syntax method against: 1) the conceptual diagram in the City's official manual that renders the acceptable adjacency conditions, and; 2) numerous real-world 2030 Youth Housing cases enlisted in the City's public notices that permit their construction. The consequences are that the axial map is not applicable whereas the convex map is adequate for the purpose at hand, and, among all the cases, those spaces that are adjacent with its Depth of less than 2 are seen to successfully satisfy the official adjacency condition for the up-zoning.

• Journal of Korean Home Economics Education Association
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• v.31 no.2
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• pp.113-135
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• 2019

The purpose of this study was to analyze the characteristics reflected in the 2015 revised home economics curriculum for the key competencies presented in the OECD education 2030 project. The results indicate that first, in general, about 46.5% of the competencies could be classified into the skill, attitude and value category; 17% into the learning concept framework category; 24.2% into the competency development cycle category; and 12.5% into the complex competency category. Overall, the competencies of the OECD learning framework are found to be reflected primarily in the achievement standards(59%), followed by characteristics(16.1%), teaching-learning and assessments orientation(9.4%), content system(8%), and goals(7.6%). Second, the key competencies were reflected in the middle school curriculum, more often in the descending order of action, problem-solving, communication, respect, creative thinking, conflict resolution, empathy, critical thinking, self-regulation, and student agency. In the high school curriculum, the competencies were reflected more often in the descending order of action, empathy, problem-solving, anticipation, global competence, self-regulation, student agency, literacy for sustainable development, reflection, and critical thinking. Third, the heat map shows that the competencies corresponding to the third and fourth levels are most frequently reflected in the curriculum. Therefore, it is advisable to develop effective plans to execute and support the reflection of key competencies in the curriculum. Through this study, home economics educators are expected to understand the inter-connectivity between the key competencies emphasized by the OECD learning framework and the competencies of home economics as a practical subject, and to scrutinize how to help individual students develop their overall competencies and be prepared for the future.

• Korea journal of population studies
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• v.31 no.1
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• pp.27-54
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• 2008

The purpose of this study is to analyze the effect of policy boosting fertility and labor participation rate on potential GDP growth rate. To do this, we employ a growth accounting approach, which decomposes per capita GDP into two parts. The first one is the change of dependency ratio and the other is the change of labor input. The labor input is again decomposed into the qualitative and quantitative parts. The quantitative part considers the change of labor participation rate and working time. The qualitative aspects is based on the trend of productivity of labor. From the scenarios of NSO(National Statistics Office), the effect of the fertility-raising policy on per capita potential GDP growth rate is calculated and projected to the year of 2050. We also forecast the policy effect inducing high labor participating rate of female labor and beyond 55-year old labor. The baseline results show that the per capita GDP growth rate will show mid 4% to the year of 2010, gradually declining to 3.94% by 2020, 3.03% by 2030, 2.41% by 2040. The high fertility rate scenario will not have effects on the potential growth by 2030, but show 0.10%p higher per capita GDP growth rate than that of baseline scenario result. By the high female labor participation policy, the per capita GDP growth rate will reach 0.04%p higher per capita GDP growth rate than that of baseline scenario. Based on the results of this paper, we conclude that the quantitative labor input cannot solely account for the trend decline of potential GDP, and the qualitative aspect, like labor productivity, is much more important element to sustain and boots the economic growth.

• International Area Studies Review
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• v.13 no.3
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• pp.331-359
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• 2009

We forecast the performance of the Korean biotechnology industry by adopting similar development paths taken by the U.S. biotechnology and Korean ICT industries. Our long-term forecasting techniques predict that Korean BT market size will increase from 3.7 billion to 10.8 billion U.S. dollars by year 2030. The pharmaceutical industry, one of major bio-subindustries, is expected to dominate Korean BT market in the long-run. Also, the relative portion of the exports in the Korean BT industry will be larger and thus the export-oriented government policy is required for the long-run growth of the Korean BT industry. Since the Korean ICT industry has already slowed down in the development, Korean BT industry is likely to catch up with ICT industry in the near future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.108-114
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• 2021

Green colored citrus is the immature fruit of the field citrus crop in Jeju, and its demand has been growing recently as it is known to contain a large amount of carotinoid, pectin, and vitamin C. It differs from the traditional varieties of blue tangerine, which are green in February and turn in yellow in March-April. This study analyzed the effects of the increased demand in green citrus on the field citrus industry. For our analysis, a partial equilibrium supply-demand model was established with a dynamic recursive structure using data from 1989-2017. Model calibration was also conducted to determine the best supply-demand model and then, the impacts of increasing demand for green immature citrus in Jeju for 2018-2030 was simulated. The simulation results show that there is no significant impact on the producing area prior to 2022, but there is a distinguishable increase of 18ha in 2023, 52ha in 2025, and 142ha in 2030. It was also predicted that revenue would increase by KRW 7.75 billion on average from 2021-2030.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.187-197
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• 2008

This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.215-224
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• 2008

The effect of streamflow considering future land use change and vegetation index information by climate change scenario was assessed using SLURP (Semi-distributed Land-Use Runoff Process) model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for the upstream watershed ($260.4km^2$) of Gyeongan water level gauging station. By applying CA-Markov technique, the future land uses (2030, 2060, 2090) were predicted after test the comparison of 2004 Landsat land use and 2004 CA-Markov land use by 1996 and 2000 land use data. The future land use showed a tendency that the forest and paddy decreased while urban, grassland and bareground increased. The future vegetation indices (2030, 2060, 2090) were estimated by the equation of linear regression between monthly NDVI of NOAA AVHRR images and monthly mean temperature of 5 years (1998-2002). Using CCCma CGCM2 simulation result based on SRES A2 and B2 scenario (2030s, 2060s, 2090s) of IPCC and data were downscaled by Stochastic Spatio-Temporal Random Cascade Model (SST-RCM) technique, the model showed that the future runoff ratio was predicted from 13% to 34% while the runoff ratio of 1999-2002 was 59%. On the other hand, the impact on runoff ratio by land use change showed about 0.1% to 1% increase.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.45-58
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• 2024

Drought risk is expected to increase as the frequency, intensity, and duration of droughts increase due to climate change. Drought risk is related to not only hydro-meteorological factors, but also water supply and demand. Recently, along with climate change, socioeconomic factors have also been recognized to increase drought risk. Therefore, it is necessary to outlook the drought risk considering various conditions for coping with future extreme droughts in a timely manner. In addition, considering various drought scenarios help reduce the uncertainty in future drought outlook. In this study, drought scenarios considering climate change scenarios, population, and water demand were created to outlook drought risk for 160 administrative districts in Korea, then new levels of drought risk were assigned based on the results of drought risk outlook to suggest drought management measures. The results showed that the drought risk will increase in the future in 2020, 2025, and 2030, compared to past. Especially the drought risk is likely twice as high in 2030 under the baseline and high scenarios. Applying the drought outlook results from this study to the new methodology for setting the risk levels shows that most regions are in Response (V) in 2020 and 2030 for baseline and high scenarios.