• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.253-273
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• 2022

Automated vehicles rely on information collected through sensors to drive. Therefore, the uncertainty of the information collected from a sensor is an important to address. To this end, research is conducted in the field of road and traffic to solve the uncertainty of these sensors through infrastructure or facilities. Therefore, this study developed a traffic cone that can maintaing the gaze guidance function in the construction site by securing sufficient LiDAR detection performance even in rainy conditions and verified its improvement effect through demonstration. Two types of cones were manufactured, a cross-type and a flat-type, to increase the reflective performance compared to an existing cone. The demonstration confirms that the flat-type traffic cone has better detection performance than an existing cone, even in 50 mm/h rainfall, which affects a driver's field of vision. In addition, it was confirmed that the detection level on a clear day was maintained at the 20 mm/h rain for both cones. In the future, improvement measures should be developed so that the traffic cones, that can improve the safety of automated driving, can be applied.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.80-90
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• 2022

Currently, the domestic early warning system is issued differently for each disaster, and is operated independently by relevant organizations from central government to local governments. Representative domestic disaster warning systems include disaster broadcasting using CBS(Cell Broadcasting Service) and DMB(Digital Multimedia Broadcasting) Automatic Emergency Alert Service, DITS(Disaster Information Transform System) transmitted and displayed on TV screens, automatic response system, automated rainfall warning system, and disaster message board. However, due to the difference in the method of issuing each emergency alert at the site of an emergency disaster, the alerts are issued at different times for each media, and the delivered content is also not integrated. If these systems are integrated, it is expected that damage to people's property and lives will be minimized by sharing and integrated management of disaster information such as voice, video, and data to comprehensively judge and make decisions about disaster situations. Therefore, in this study, we present a plan for the integration of the disaster warning system along with the analysis of the operation status of the domestic early warning system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.5-11
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• 2023

Economic damage is occurring due to landslides and debris flows that occur when the ground artificially created for roads or photovoltaic power generation facilities is weakened by rainfall such as torrential rain. In order to understand the stability of the artificially created ground, it is very important to check the ground information such as the compositional state and mechanical characteristics of the stratum. However, since most of the investigation sites are steep slopes or there are no access roads, it is not easy to enter the drilling equipment commonly used to check ground information and perform standard penetration tests. In this study, a dynamic cone penetration test (DCP) device using a miniaturized auger drilling equipment and an automatic drop device was developed to check the cone resistance value and the dynamic cone penetration test value and analyze the correlation with the standard penetration test value to confirm its applicability at the mountain solar power generation site. As a result, the cone resistance value is q_d = 0.46 N and the dynamic cone penetration test value is N_d = 1.58 N, confirming a value similar to the results of existing researchers to secure its reliability.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.199-207
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• 2024

Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

• Journal of Korean Society of Forest Science
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• v.45 no.1
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• pp.11-25
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• 1979

There was much mass movement at many different mountain side of Peong Chang area in Kwangwon province by the influence of heavy rainfall through August/4 5, 1979. This study have done with the fact observed through the field survey and the information of the former researchers. The results are as follows; 1. Heavy rainfall area with more than 200mm per day and more than 60mm per hour as maximum rainfall during past 6 years, are distributed in the western side of the connecting line through Hoeng Seong, Weonju, Yeongdong, Muju, Namweon and Suncheon, and of the southern sea side of KeongsangNam-do. The heavy rain fan reason in the above area seems to be influenced by the mouktam range and moving direction of depression. 2. Peak point of heavy rainfall distribution always happen during the night time and seems to cause directly mass movement and serious damage. 3. Soil mass movement in Peongchang break out from the course sandy loam soil of granite group and the clay soil of lime stone and shale. Earth have moved along the surface of both bedrock or also the hardpan in case of the lime stone area. 4. Infiltration seems to be rapid on the both bedrock soil, the former is by the soil texture and the latter is by the crumb structure, high humus content and dense root system in surface soil. 5. Topographic pattern of mass movement spot is mostly the concave slope at the valley head or at the upper part of middle slope which run-off can easily come together from the surrounding slope. Soil profile of mass movement spot has wet soil in the lime stone area and loose or deep soil in the granite area. 6. Dominant slope degree of the soil mass movement site has steep slope, mostly, more than 25 degree and slope position that start mass movement is mostly in the range of the middle slope line to ridge line. 7. Vegetation status of soil mass movement area are mostly fire field agriculture area, it's abandoned grass land, young plantation made on the fire field poor forest of the erosion control site and non forest land composed mainly grass and shrubs. Very rare earth sliding can be found in the big tree stands but mostly from the thin soil site on the un-weatherd bed rock. 8. Dangerous condition of soil mass movement and land sliding seems to be estimated by the several environmental factors, namely, vegetation cover, slope degree, slope shape and position, bed rock and soil profile characteristics etc. 9. House break down are mostly happen on the following site, namely, colluvial cone and fan, talus, foot area of concave slope and small terrace or colluvial soil between valley and at the small river side Dangerous house from mass movement could be interpreted by the aerial photo with reference of the surrounding site condition of house and village in the mountain area 10. As a counter plan for the prevention of mass movement damage the technics of it's risk diagnosis and the field survey should be done, and the mass movement control of prevention should be started with the goverment support as soon as possible. The precautionary measures of house and village protection from mass movement damage should be made and executed and considered the protecting forest making around the house and village. 11. Dangerous or safety of house and village from mass movement and flood damage will be indentified and informed to the village people of mountain area through the forest extension work. 12. Clear cutting activity on the steep granite site, fire field making on the steep slope, house or village construction on the dangerous site and fuel collection in the eroded forest or the steep forest land should be surely prohibited When making the management plan the mass movement, soil erosion and flood problem will be concidered and also included the prevention method of disaster.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of Korean Society of Forest Science
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• v.88 no.4
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• pp.498-509
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• 1999

This study aims to clarify the effect of forest management practices(thinning and pruning) in forest hydrological processes on electrical conductivity to get the fundamental information on the facilitation of purifying water quality after forestry practices. Rainfall, throughfall, stemflow, soil and stream water were sampled at the study sites which consist of Abies holophylla and Pinus koraiensis in Kwangnung Experimental Forest for 6 months from March 1 to August 4, 1998. In case of deviding into forest hydrological processes, multiple regression equations of electrical conductivity and total amount of anion, $NO{_3}^-$ of throughfall, stemflow, soil water of management site in Abies holophylla shows high significance. And multiple regression equations of electrical conductivity and total amount of anion, $SO{_4}^{2-}$, $Cl^-$ of throughfall, stemflow, soil water of non-management site in Abies holophylla shows high significance. Multiple regression equations of electrical conductivity and $NO{_3}^-$, before non-rain days of throughfall, stemflow, soil water of management site in Pinus koraiensis shows high significance. And multiple regression equations of electrical conductivity and total amount of ion, $NO{_3}^-$, $K^+$, pH, total amount of anion of throughfall, stemflow, soil water of non-management site in Plinus koraiensis shows high significance. Multiple regression equations of electrical conductivity and pricipitation, total amount of ion, $Na^+$ of stream water in Abies holophylla and Pinus koraiensis shows high significance. In case of combining into forest hydrological processes, multiple regression equations of electrical conductivity and total amount of cation and anion, $Na^+$, $Cl^-$, and pH in rainfall, throughfall, stemflow, soil and stream water shows high significance.

• Korean Journal of Soil Science and Fertilizer
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• v.20 no.3
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• pp.285-299
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• 1987

Timing and placement of fertilizer applications are two managerial means to improve the fertilizer use efficiency. The relative importance of these two means is determined by the application rate. With the realistic rate of N application recommended to the small farmers in the tropics, at present and in the near future, basal application in right manner, seems to be more important than split application at different times. In wetland rice soils, deep placement by whatever available means is desirable. But in the situations where perfect deep placement is very difficult to implement, the whole-layer application may be worth trying, until better methods become available. In rainfed uplands, N fertilizer application plans should be contingent upon the amount and distribution of rainfall: apply a less risky rate as subsurface banding near the crop rows to start with; then, depending upon the rainfall prospects in the season, apply or omit the additional dose. Because the patterns of crop response to N fertilizer can be significantly different between the research farms and farmers' fields, it seems imperative to have information on the patterns of crop response to N under farmers' management conditions, for the development of realistic fertilizer application recommendations. To enable the farmers to adopt improved fertilizer application technologies, it is essential to develop and make available to farmers convenient fertilizer applicators. Past experience with the improved fertilizer use technologies indicates that, in the long run, the development of fertilizers that are not only effective and convenient for farmers to use but also easy to produce without major modifications of existing fertilizer production systems is the ultimate solution to the problem of low N fertilizer use efficiency.