• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1166-1175
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• 2021

We investigate the current situation and development trend of domestic smart city and emergency vehicle priority signal control system analyzing the existing effectiveness of 1) emergency vehicle priority signal control system and 2) control emergency vehicle priority signal, based on domestic and foreign prior research for signal control system security. The effectiveness of time reduction was analyzed through actual application and test operation to emergency vehicles after establishing the system. In addition, for security management and stable service of real-time signal system control we propose improvement for the technical control items of the ISMS-P certification system to secure golden time to protect citizens' precious lives and property in case of emergency by classifying and mapping the existing ISMS-P certification system and the Korea Internet & Security Agency's cyber security guide according to the items of security threats.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.963-978
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• 2020

Earthquakes can induce a large number of landslides and cause very serious property damage and human casualties. There are two issues in study on earthquake-induced landslides: (1) slope stability analysis under seismic loading and (2) debris flow run-out analysis. This study aims to review technical studies related to the development and application of earthquake-induced landslide models (seismic slope stability analysis). Moreover, a pilot application of a physics-based slope stability model to Mt. Umyeon, in Seoul, with several earthquake scenarios was conducted to test regional scale seismic landslide mapping. The earthquake-induced landslide simulation model can be categorized into 1) Pseudo-static model, 2) Newmark's dynamic displacement model and 3) stress-strain model. The Pseudo-static model is preferred for producing seismic landslide hazard maps because it is impossible to verify the dynamic model-based simulation results due to lack of earthquake-induced landslide inventory in Korea. Earthquake scenario-based simulation results show that given dry conditions, unstable slopes begin to occur in parts of upper areas due to the 50-year earthquake magnitude; most of the study area becomes unstable when the earthquake frequency is 200 years. On the other hand, when the soil is in a wet state due to heavy rainfall, many areas are unstable even if no earthquake occurs, and when rainfall and 50-year earthquakes occur simultaneously, most areas appear unstable, as in simulation results based on 100-year earthquakes in dry condition.

• Journal of Korean Society of Water Science and Technology
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• v.26 no.6
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• pp.133-142
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• 2018

Increasing localized torrential rainfall caused by abnormal climate are making higher damage to human and property through urban inundation So The need of preventive measures is being highlighted. In this study, the methodology for calculating flood depth in domestic water map using an interpolation method in order to utilizing the results of flood analysis provided only in the form of a report is suggested. In the Incheon Metropolitan City S area as the test-bed, the flood depth was calculated using the interpolating the actual flood analysis by image and verification was performed. Verification results showed that the error rate was 5.2% for the maximum flooding depth, and that the water depth value was compared to 10 random points, which showed a difference of less than 0.030 m. Also, as the results of the flood analysis were presented in various ways, the flood depth was extracted from the image of the result of the flood analysis, which changed the presentation method, and then compared and analyzed. The results of this study could be available for the use of basic data from the research on the urban penetration of domestic consumption and for decision-making of policy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.393-402
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• 2022

Effective data management of underground facilities is very important in terms of human life. For this, input of up-to-date and high-accuracy data should be preceded. Therefore, it is important to have an efficient data input method. In this study, by developing a sewage facility site survey program using open source software, paper drawings could be replaced with tablet PCs. By using a tablet PC, figures and property information acquired from the field are transmitted in real time through a database server. PostGIS query is developed to automate structured editing to minimize manual work in constructing a GIS (Geographic Information System) database for sewage facilities. did. In addition, the database was built using the sewage facility GIS database building program. As a result of comparing and analyzing the existing sewage facility database construction, work process, and work time, the work process was simplified and work time was shortened. In addition, through simple customization of open source software, it will be able to be used for field surveys and database construction in other fields.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.248-248
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• 2023

In recent years, the number of landslides in Korea has been increasing due to extreme weather events such as localized heavy rainfall and typhoons. Landslides often occur with debris flows, land subsidence, and earthquakes. They cause significant damage to life and property. 64% of Korea's land area is made up of mountains, the government wanted to predict landslides to reduce damage. In response, the Korea Forest Service has established a 'Landslide Information System' to predict the likelihood of landslides. This system selects a total of 13 landslide factors based on past landslide events. Using the LR technique (Logistic Regression) to predict the possibility of a landslide occurrence and the accuracy is known to be 0.75. However, most of the data used for learning in the current system is on landslides that occurred from 2005 to 2011, and it does not reflect recent typhoons or heavy rain. Therefore, in this study, we will apply a total of six machine learning techniques (KNN, LR, SVM, XGB, RF, GNB) to predict the occurrence of landslides based on the data of Inje, Gangwon-do, which was recently produced by the National Institute of Forest. To predict the occurrence of landslides, it is necessary to process converting landslide events and factors data into a suitable form for machine learning techniques through ArcGIS and Python. In addition, there is a large difference in the number of data between areas where landslides occurred or not. Therefore, the prediction was performed after correcting the unbalanced data using Tomek Links and Near Miss techniques. Moreover, to control unbalanced data, a model that reflects soil properties will use to remove absolute safe areas.

• Journal of Korean Library and Information Science Society
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• v.54 no.2
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• pp.1-22
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• 2023

In this study, we propose a plan to reflect LRM in various library-related standards or systems through analyzing the reflection of LRM in RDA. To this end, LRM and RDA 2020 were analyzed in terms of entities, relationships, attributes, and encoding schemes. First of all, for the mapping of entities, relationships, and attributes, all properties and relationships were extracted for each entity of RDA, LRM elements corresponding to each property and relationship were found and mapped, and encoding schemes were additionally compared. As a result, the things to consider in the standards and systems to which LRM is to be applied are: first, entities development considering the LRM hierarchy; second, new relation or shortcut path relation development; third, attributes expansion according to the entities considering the LRM hierarchical structure, and fourth, the development of various encoding scheme. Through this study, it will be possible to find an application plan using the application of RDA as a model in standards or systems to accept LRM.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.51-65
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• 2024

Landslides are natural disasters that causes significant property damage worldwide every year. In Korea, damage due to landslides is increasing owing to the effects of climate change, and it is important to identify the factors that increase the prevalence of landslides in order to reduce the damage they cause. Therefore, this study used a random forest model to analyze the importance of 14 factors in influencing landslide damage in a specific area of Chungju, Chungcheongbuk-do province, Korea. The random forest model performed accurately with an AUC of 0.87 and the most-important factors were ranked in the order of aspect, slope, distance to valley, and elevation, suggesting that topographic factors such as aspect and slope more greatly influence landslide damage than geological or soil factors such as rock type and soil thickness. The results of this study are expected to provide a basis for mapping and predicting landslide damage, and for research focused on reducing landslide damage.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.3
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• pp.115-120
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• 2016

$CeO_2$ is used as a co-catalyst with $TiO_2$ to improve the catalytic activity of $MnO_x$ and characterization of nano-sized powder is identified with de-NOx efficiency. A comparison between $MnO_x-CeO_2/TiO_2$ and single $CeO_2$ was conducted in terms of microstructural analysis to observe the behavior of $CeO_2$ in the ternary catalyst. The $MnO_x-CeO_2/TiO_2$ catalyst was synthesized by sol-gel method and the average particle size of the single $CeO_2$ is about $285{\mu}m$ due to the low thermal stability, whereas the particle size $MnO_x-CeO_2/TiO_2$ is about 130 nm. The strong interaction between Ce and Ti was identified through the EDS mapping by transmission electron microscopy (TEM). The improvement about 20 % of $de-NO_x$ efficiency is observed in the low-temperature ($150^{\circ}C{\sim}250^{\circ}C$) and vigorous oxygen exchange by well-dispersed $CeO_2$ is the reason of catalytic activity improvement.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.