• Journal of The Geomorphological Association of Korea
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• v.25 no.3
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• pp.1-18
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• 2018

In Korea, 64% of the land is known as mountain area, but the definition and classification standard of mountain are not clear. Demand for utilization and development of mountain area is increasing. In this situation, the unclear definition and scope of the mountain area can lead to the destruction of the mountain and the increase of disasters due to indiscreet permission of forestland use conversion. Therefore, this study analyzed the variables and criteria that can extract the mountain boundaries through the questionnaire survey and the terrain analysis. We developed a mountain boundary extraction algorithm that can classify topographic mountain by using selected variables. As a result, 72.1% of the total land was analyzed as mountain area. For the three catchment areas with different mountain area ratio, we compared the results with the existing data such as forestland map and cadastral map. We confirmed the differences in boundary and distribution of mountain. In a catchment area with predominantly mountainous area, the algorithmbased mountain classification results were judged to be wider than the mountain or forest of the two maps. On the other hand, in the basin where the non-mountainous region predominated, algorithm-based results yielded a lower mountain area ratio than the other two maps. In the two maps, we was able to confirm the distribution of fragmented mountains. However, these areas were classified as non-mountain areas in algorithm-based results. We concluded that this result occurred because of the algorithm, so it is necessary to refine and elaborate the algorithm afterward. Nevertheless, this algorithm can analyze the topographic variables and the optimal value by watershed that can distinguish the mountain area. The results of this study are significant in that the mountain boundaries were extracted considering the characteristics of different mountain topography by region. This study will help establish policies for stable mountain management.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.248-258
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• 2021

The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.255-262
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• 2021

In this study, a jointless bridge that integrates the superstructure and abutment without installing an expansion joint was analyzed. An example of a jointless bridge that has been introduced in Korea since 2009. Owing to the short period of use and lack of experience in design, construction, and maintenance, there is insufficient information regarding the long-term behavior of jointless bridges. When analyzing numerous bridges, the numerical analysis model must maintain the numerical values used and ensure the convenience of model construction. In this study, sensitivity analysis was performed to select a numerical model for various types of jointless bridges using commercial finite element programs, MIDAS Civil and ABAQUS 2018. According to a solid element-based model, we analyzed the mean and maximum relative errors between structural models. Consequently, it was found that the beam element-based model exhibits a significantly small relative error in comparison to the shell element, where a relatively large error was recorded. Therefore, the optimal numerical analysis model, a practical model that maintains the similarity and precision of the displacement shape cause by relative error, was judged to be the most suitable for jointless bridges based on the shell element.

• Journal of the Korean Geosynthetics Society
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• v.20 no.4
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• pp.19-32
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• 2021

In this study, evaluation and consideration of domestic/overseas design, construction, and quality control performed by the authors on the deep cement mixing method were performed, and improvements for the development of the DCM method were suggested in the future. As a result of this study, it was found that the cross-sectional area correction for strength is required during the laboratory test of mix proportion, and caution is required because the extrapolation method may lead to different results from the actual one. Applicable design methods should be selected in consideration of both the improvement ratio and the type of improvement during design, and it was confirmed that the allowable compressive strength to which the safety factor was applied refers to the standard value for stability review and not the design parameters. In the case of the stress concentration ratio, rather than applying a conventional value, it was possible to perform economical design by calculating the experimental and theoretical stress concentration ratio reflecting the design conditions. In the case where pre-boring is expected during construction, if the increased water content is not large compared to the original, there were cases where a major problem did not occur even if the result that did not consider the increase in water content was used. In addition, it was confirmed that when the ratio of the top treatment length to the improved length is high, a small amount of design cement contents per unit length can be injected during construction. In the case of quality control, it was evaluated that D/4~2D/4 for single-axis and D/4 point for multi-axis were optimal for coring of grouting mixtures. As an item for quality control, it is judged that the standard that considers the TCR along with the unconfined compressive strength of grouting mixtures is more suitable for the domestic situation.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.120-130
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• 2022

In this study, the applicability of the microseismic monitoring system based on the underground mine communication system has been verified by operation test in the domestic underground mine. The microseismic data consists of wavelet data and meta-data for mine safety management, and both data should be transferred, stored, analyzed and managed with proper method according to the purpose and size of each data. In order to select the optimal communication system for the microseismic monitoring system considering the underground environment as well as properties of data, various types of communication system have been tested and compared during operation test after installing the optical cable communication system, 2.4 GHz and 900 MHz wireless communication system through the underground mine tunnel and overground area of the test site. The integrated microseismic monitoring software, which was developed to secure the stability of data management and ease of use, has been updated according to findings from operation test. Through the operation test of the microseismic monitoring system including the communication system and the monitoring software, the technical basis was established corresponding to various requirements of the domestic mine for adoption of the microseismic monitoring system.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.85-94
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• 2022

Construction industry is facing difficult challenges in terms of productivity, manpower, and industrial accidents. Currently, along with the 4th Industrial Revolution, various high-tech technologies are emerging, and efforts are being made to solve the problem by applying the technologies related to the 4th Industrial Revolution to the construction industry. As part of these efforts, research is being conducted to develop a construction equipment control system to increase productivity and safety at earthworks sites where many and various types of construction equipment are involved, and the system needs a function to increase productivity by optimizing the moving path of construction equipment. In the case of trucks, the location of the temporary road must be optimized in order to optimize the path of movement in the construction site. However, only matters related to the quality standard of temporary roads have been suggested so far, and there is no standardized process for efficiently determining the location of temporary roads. In this paper, the factors and its importance related to the location of the temporary road were identified through field surveys and interviews with experts, and a method for determining the location of the temporary road was presented. It was confirmed that the suggested method through a case study could improve the productivity of earthwork.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.