• Maritime Security
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• v.1 no.1
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• pp.273-310
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• 2020

This study aims at empirically analyzing the overall mechanism of the "Gray Zone Strategy", which has begun to be used as one of Chinese major maritime security strategies in maritime conflicts surrounding the South China Sea and East China Sea since early 2010, and comparing the resulting conflict patterns in those reg ions. To this end, I made the following two hypotheses about Chinese gray zone strategy. The hypotheses that I have argued in this study are the first, "The marine gray zone strategy used by China shows different structures of implementation in the South China Sea and the East China Sea, which are major conflict areas.", the second, "Therefore, the patterns of disputes in the South China Sea and the East China Sea also show a difference." In order to examine this, I will classify Chinese gray zone strategy mechanisms multi-dimensionally in large order, 1) conflict trends and frequency of strategy execution, 2) types and strengths of strategy, 3) actors of strategy execution, and 4) response methods of counterparts. So, I tried to collect data related to this based on quantitative modeling to test these. After that, about 10 years of data pertaining to this topic were processed, and a research model was designed with a new categorization and operational definition of gray zone strategies. Based on this, I was able to successfully test all the hypotheses by successfully comparing the comprehensive mechanisms of the gray zone strategy used by China and the conflict patterns between the South China Sea and the East China Sea. In the conclusion, the verified results were rementioned with emphasizing the need to overcome the security vulnerabilities in East Asia that could be caused by China's marine gray zone strategy. This study, which has never been attempted so far, is of great significance in that it clarified the intrinsic structure in which China's gray zone strategy was implemented using empirical case studies, and the correlation between this and maritime conflict patterns was investigated.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• 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.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.289-308
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• 2021

This study conducts coupled thermo-hydro-mechanical numerical modeling to investigate the maximum temperature and conditions for securing mechanical stability of the high-level radioactive waste repository when temperature criteria of bentonite buffer are 100℃ and 125℃, respectively. In case of temperature criterion of buffer as 100℃, the maximum temperatures at the interface between canister and buffer are calculated to be 99.4℃ and 99.8℃, respectively for a case with disposal tunnel spacing of 40 m and deposition hole spacing of 5.5 m and for the other case with disposal tunnel spacing of 30 m and deposition hole spacing of 6.5 m. In case of temperature criterion of buffer as 125℃, spacings of disposal tunnel and deposition hole could be decreased to 30 m and 4.5 m, respectively, which reduces the disposal area up to 55% compared to the disposal area of KRS⁺. According to analysis of mechanical stability for various disposal spacings, RMR of rock mass for KRS⁺ should be larger than 72.4 which belongs to good rock in RMR classification to prevent failure of rock mass. As disposal spacing is decreased, required RMR of rock mass is increased. In order to prevent failure of rock mass for a case with disposal tunnel spacing of 30 m and deposition hole spacing of 4.5 m, RMR larger than 87.3 is needed. However, mechanical stability of the repository is secured for all cases with RMR over 75 considering the enhancement of rock strength due to confining stress induced by swelling of the bentonite buffer and backfill.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.662-676
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• 2021

The Yeosu Sado dinosaur tracksite is well known for many dinosaur tracks and research on the gregarious behavior of dinosaurs. In addition, various geological and geographical heritage sites are distributed on Sado Island. However, educational field trips for students are very limited due to accessibility according to its geological location, time constraints due to tides, and continuous weathering and damage. Therefore, this study aims to generate 3D models and images of dinosaur tracks using the photogrammetric method, which has recently been used in various fields, and then discuss the possibility of using them as paleontological research and educational contents. As a result of checking the obtained 3D images and models, it was possible to confirm the existence of footprints that were not previously discovered or could not represent details by naked eyes or photos. Even previously discovered tracks could possibly present details using 3D images that could not be expressed by photos or interpretive drawings. In addition, the 3D model of dinosaur tracks can be preserved as semi-permanent data, enabling various forms of utilization and preservation. Here we apply 3D printing and mobile augmented reality content using photogrammetric 3D models for a virtual field trip, and these models acquired by photogrammetry can be used in various educational content fields that require 3D models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.366-373
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• 2021

This study attempted to establish a field data-based write analysis standard by analyzing field observation data, which is non-linear data of southern garlic. Five regions, including Goheung, Namhae, Sinan, Changnyeong, and Haenam, were selected for analysis. Observation values for each observation station were extracted from the temperature data of farmland in the region through inverse distance weighted. Southern-type garlic production and temperature data were collected for 10 years, from 2010 to 2019. Local regression analysis (Kernel) of the obtained data was performed, and growth temperatures were analyzed, such as 0.8 (18.781℃), 0.9 (18.930℃), 1.0 (19.542℃), 1.1 (20.165℃), and 1.2 (21.042℃) depending on the bandwidth. The analyzed optimum temperature and the grown temperature (4℃/25℃) were applied to extract the growth temperature for each temperature by using the temperature response model analysis. Regression analysis and correlation analysis were performed between the analyzed growth temperature and production data. The coefficient of determination(R²) was analyzed as 0.325 to 0.438, and in the correlation analysis, the correlation coefficient of 0.57 to 0.66 was analyzed at the significance probability 0.001 level. Overall, as the bandwidth increased, the coefficient of determination was higher. However, in all analyses except bandwidth 1.0, it was analyzed that all variables were not used due to bias. The purpose of this study is to accommodate all data through non-linear data. It was analyzed that bandwidth 1.0 with a high coefficient of determination while accepting modeling as a whole is the most suitable.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.49-71
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• 2021

Users who intend to utilize knowledge to actively solve given problems proceed their jobs with cross- and sequential exploration of associated knowledge related each other in terms of certain criteria, such as content relevance. A knowledge map is the diagram or taxonomy overviewing status of currently managed knowledge in a knowledge-base, and supports users' knowledge exploration based on certain relationships between knowledge. A knowledge map, therefore, must be expressed in a networked form by linking related knowledge based on certain types of relationships, and should be implemented by deploying proper technologies or tools specialized in defining and inferring them. To meet this end, this study suggests a methodology for developing the knowledge graph-based knowledge map using the Graph DB known to exhibit proper functionality in expressing and inferring relationships between entities and their relationships stored in a knowledge-base. Procedures of the proposed methodology are modeling graph data, creating nodes, properties, relationships, and composing knowledge networks by combining identified links between knowledge. Among various Graph DBs, the Neo4j is used in this study for its high credibility and applicability through wide and various application cases. To examine the validity of the proposed methodology, a knowledge graph-based knowledge map is implemented deploying the Graph DB, and a performance comparison test is performed, by applying previous research's data to check whether this study's knowledge map can yield the same level of performance as the previous one did. Previous research's case is concerned with building a process-based knowledge map using the ontology technology, which identifies links between related knowledge based on the sequences of tasks producing or being activated by knowledge. In other words, since a task not only is activated by knowledge as an input but also produces knowledge as an output, input and output knowledge are linked as a flow by the task. Also since a business process is composed of affiliated tasks to fulfill the purpose of the process, the knowledge networks within a business process can be concluded by the sequences of the tasks composing the process. Therefore, using the Neo4j, considered process, task, and knowledge as well as the relationships among them are defined as nodes and relationships so that knowledge links can be identified based on the sequences of tasks. The resultant knowledge network by aggregating identified knowledge links is the knowledge map equipping functionality as a knowledge graph, and therefore its performance needs to be tested whether it meets the level of previous research's validation results. The performance test examines two aspects, the correctness of knowledge links and the possibility of inferring new types of knowledge: the former is examined using 7 questions, and the latter is checked by extracting two new-typed knowledge. As a result, the knowledge map constructed through the proposed methodology has showed the same level of performance as the previous one, and processed knowledge definition as well as knowledge relationship inference in a more efficient manner. Furthermore, comparing to the previous research's ontology-based approach, this study's Graph DB-based approach has also showed more beneficial functionality in intensively managing only the knowledge of interest, dynamically defining knowledge and relationships by reflecting various meanings from situations to purposes, agilely inferring knowledge and relationships through Cypher-based query, and easily creating a new relationship by aggregating existing ones, etc. This study's artifacts can be applied to implement the user-friendly function of knowledge exploration reflecting user's cognitive process toward associated knowledge, and can further underpin the development of an intelligent knowledge-base expanding autonomously through the discovery of new knowledge and their relationships by inference. This study, moreover than these, has an instant effect on implementing the networked knowledge map essential to satisfying contemporary users eagerly excavating the way to find proper knowledge to use.