• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.45-52
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• 2008

The objectives of this study are to explain a supply plan of domestic softwood log by long-term prospect of MDF production to stably promote industry of MDF. For it, we developed the long supply function as Ordinary Least Squares Method. Between 2005 and 2050, it was estimated that quantity of domestic production of MDF increased from 1,653 thousand $m^3$ to 2,041 thousand $m^3$. In 2050, quantities of domestic softwood log used by raw materials to product MDF of 2,041 thousand $m^3$ were estimated to be used about 1,355 thousand $m^3$. Exampling Pinus rigida used presently by raw materials to product MDF, cutting area of it is estimated to be 10,828 ha per year. And larch is cutted about 9,160 ha per year. This study estimated annual softwood log cutting amount and total afforestation area at 2050 year by 3 scenarios which are 35%, 45% and 55% about use of domestic softwood log for MDF production. If we do a criterion of cutting area, we advantage to plant larch. But the species of trees are use and growth property. We think that the afforestation policy must be performed on the base of those to supply raw materials of MDF. Although government plans hardwood afforestation policy after cutting Pinus rigida, it needs to support and manage certainly afforestation area of softwoods to need to supply raw materials of MDF to stably promote industry of MDF.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.7-16
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• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Journal of Climate Change Research
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• v.3 no.3
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• pp.183-193
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• 2012

In this study, the S University's energy usage, greenhouse gas emissions situation and potential reduction amount were analyzed using a long-term energy analysis model, LEAP. In accordance with the VISION 2020 and university's own improvement plans, S University plans to complete a second campus through expansion constructions by 2020 and by allocating the needed land. Accordingly, increases in energy usage and greenhouse gas emissions seem inevitable. Hence, in this study, the calculations of potential reduction amount by 2020 were attempted through the use of LEAP model by categorizing the energy used based on usage types and by proposing usage typebased reduction methods. There were a total of 4 scenarios: a standard scenario that predicted the energy usage without any additional energy reduction activity; energy reduction scenario using LED light replacement; energy reduction scenario using high efficiency building equipment; and a scenario that combines these two energy reduction scenarios. As scenario-based results, it was ascertained that, through the scenario that had two other energy reduction scenarios combined, the 2020 greenhouse gas emissions amount would be 14,916 tons of $CO_2eq$, an increase of 43.7% compared to the 2010 greenhouse gas emissions amount. Put differently, it was possible to derive a result of about 23.7% reduction of the greenhouse gas emissions amount for S University's greenhouse gas emissions amount through energy reduction activities. In terms of energy reduction methods, changing into ultra-high efficiency building equipment would deliver the most amount of reduction.

• Korean Journal of Environmental Biology
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• v.41 no.3
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• pp.204-214
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• 2023

This study aimed to conduct a comprehensive assessment of the potential impact of deforestation and forest restoration on carbon storage in North Korea until 2050, employing rigorous analyses of trends of land use change in the past periods and projecting future land use change scenarios. We utilized the CA-Markov model, which can reflect spatial trends in land use changes, and verified the impact of forest restoration strategies on carbon storage by creating land use change scenarios (reforestation and non-reforestation). We employed two distinct periods of land use maps (2000 to 2010 and 2010 to 2020). To verify the overall terrestrial carbon storage in North Korea, our evaluation included estimations of carbon storage for various elements such as above-ground, below-ground, soil, and debris (including litters) for settlement, forest, cultivated, grass, and bare areas. Our results demonstrated that effective forest restoration strategies in North Korea have the potential to increase carbon storage by 4.4% by the year 2050, relative to the carbon storage observed in 2020. In contrast, if deforestation continues without forest restoration efforts, we predict a concerning decrease in carbon storage by 11.5% by the year 2050, compared to the levels in 2020. Our findings underscore the significance of prioritizing and continuing forest restoration efforts to effectively increase carbon storage in North Korea. Furthermore, the implications presented in this study are expected to be used in the formulation and implementation of long-term forest restoration strategies in North Korea, while fostering international cooperation towards this common environmental goal.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.591-597
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• 2011

Forest carbon stock changes in a national forest were assessed by CBM-CFS3 model with different management scenarios to support decision making for a long term forest planning. Management scenarios were composed with 4 different levels of timber harvesting - current harvesting level (scenario1), 30% increment in each period (scenario2), 3 times increment (scenario3), and 5 times increment (scenario4). For each scenarios, changes in total carbon stocks, carbon stocks of each carbon pools, carbon stocks of harvested wood products (HWP) and age class structure were estimated over 100-year planning horizon. The estimated total carbon stock including HWP at the end of final period (100 years) was 433.1 tC/ha under scenario 1, but the age class structure has skewed right to the upper classes, which is not desirable for sustainable forest management. Under the scenario 4, however, the total carbon stock decrease to 385.5 tC/ha and the area of old growth forest show a significant decline. The estimated total carbon stock under scenario 2 and 3 were 411.7 tC/ha and 410.5 tC/ha respectively, and it was able to maintain the initial level of the forest carbon stocks during the planning horizon. Also the age class structures under the scenario 2 and 3 were evenly distributed from class 1 to class 8. Overall, scenario 2 and 3 were the most acceptable forest management options, in terms of carbon stock changes and age class structure.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Journal of Climate Change Research
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• v.2 no.1
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• pp.55-68
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• 2011

The Intergovernmental Panel on Climate Change(IPCC) has identified the causes of climate change and come up with measures to address it at the global level. Its key component of the work involves developing and assessing future climate change scenarios. The IPCC Expert Meeting in September 2007 identified a new greenhouse gas concentration scenario "Representative Concentration Pathway(RCP)" and established the framework and development schedules for Climate Modeling (CM), Integrated Assessment Modeling(IAM), Impact Adaptation Vulnerability(IAV) community for the fifth IPCC Assessment Reports while 130 researchers and users took part in. The CM community at the IPCC Expert Meeting in September 2008, agreed on a new set of coordinated climate model experiments, the phase five of the Coupled Model Intercomparison Project(CMIP5), which consists of more than 30 standardized experiment protocols for the shortterm and long-term time scales, in order to enhance understanding on climate change for the IPCC AR5 and to develop climate change scenarios and to address major issues raised at the IPCC AR4. Since early 2009, fourteen countries including the Korea have been carrying out CMIP5-related projects. Withe increasing interest on climate change, in 2009 the COdinated Regional Downscaling EXperiment(CORDEX) has been launched to generate regional and local level information on climate change. The National Institute of Meteorological Research(NIMR) under the Korea Meteorological Administration (KMA) has contributed to the IPCC AR4 by developing climate change scenarios based on IPCC SRES using ECHO-G and embarked on crafting national scenarios for climate change as well as RCP-based global ones by engaging in international projects such as CMIP5 and CORDEX. NIMR/KMA will make a contribution to drawing the IPCC AR5 and will develop national climate change scenarios reflecting geographical factors, local climate characteristics and user needs and provide them to national IAV and IAM communites to assess future regional climate impacts and take action.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.28-38
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• 2019

Climate change on the Korean peninsula is progressing faster than the global average. For example, typhoons, extreme rainfall, heavy snow, cold, and heatwave that are occurring frequently. North Korea is particularly vulnerable to climate change-related natural disasters such as flooding and flooding due to long-term food shortages, energy shortages, and reckless deforestation and development. In addition, North Korea is classified as an unmeasured area due to political and social influences, making it difficult to obtain sufficient hydrologic data for hydrological analysis. Also, as interest in climate change has increased, studies on climate change have been actively conducted on the Korean Peninsula in various repair facilities and disaster countermeasures, but there are no cases of research on North Korea. Therefore, this study selects watershed characteristic variables that are easy to acquire in order to apply localization model to North Korea where it is difficult to obtain observed hydrologic data and estimates parameters based on meteorological and topographical characteristics of 16 dam basins in South Korea. Was calculated. In addition, as a result of reviewing the applicability of the parameter estimation equations calculated for the fifty thousand, Gangneungnamdaecheon, Namgang dam, and Yeonggang basins, the applicability of the parameter estimation equations to North Korea was very high.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.595-603
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• 2016

In the Republic of Korea, the LTE-based public safety (PS-LTE) network is being built for the 700 MHz frequency band. However, the same bands are also assigned to the LTE-based high-speed railway (LTE-R) network. Therefore, it is essential to utilize the co-channel interference management schemes for the coexistence of two LTE networks in order to increase the system throughput and to reduce the user outage probability. In this paper, we focus on the downlink (DL) system for the coexistence of PS-LTE and LTE-R networks by considering non radio access network (RAN) sharing and LTE-R RAN sharing by PS-LTE users (UEs) to analyze the UE throughput. Moreover, we also utilize the cooperative communications schemes, such as coordinated multipoint (CoMP) for the coexistence of PS-LTE and LTE-R networks in order to reduce the UE outage probability. We categorize the coexistence of PS-LTE and LTE-R networks into four different scenarios, and evaluate the performance of each scenario by the important performance indexes, such as UE average throughput and UE outage probability.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.