• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.171-182
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• 2010

Water demand and resource at a watershed scale were investigated to prepare for long-term water planning of the Namgang sub-basin. The quantity of water resource was defined as average annual runoff by a simple Tank model with three serial tanks, and water demand for public, industrial, agricultural and the other uses was determined using the per-unit method employed in the Water Vision 2020, the Ministry of Construction and Transportation. The results showed that total amount of water resources in the Namgang sub-basin was estimated as about $935,414{\times}10^{3}m^3/yr$ for a 10-year period from 2000 to 2009 and the water withdrawals in public, industrial, agricultural and other sector were derived as $105,493{\times}10^{3}m^3/yr$, $32,686{\times}10^{3}m^3/yr$, $243,194{\times}10^{3}m^3/yr$, and $81,615{\times}10^{3}\;m^3m^3/yr$, respectively. In addition, the Namgaram Inno-city project could increase the overall water demand by $17,156{\times}10^{3}\;mm^3/yr$ due to the population influx.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.124-124
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• 2016

하천에서의 분변성대장균은 분변성 오염 정도를 나타내는 지표로서, 이 농도가 높을수록 오염된 하천수와의 접촉을 통한 호흡기, 소화기 및 피부 관련 질병의 발발 확률이 높다고 알려져 있다. 따라서 하천에서의 수영, 수상스키 등과 같은 입수형 친수활동을 할 때, 분변성대장균 농도가 농도 기준 이하인지를 확인하고 이러한 정보를 친수활동에 이용할 필요가 있다. 그러나 분변성대장균의 경우, 현재 자동수질측정망에서 측정되고 있는 다른 수질인자들과는 달리 실시간 측정이 불가능하다고 알려져 있다. 분변성대장균을 측정하는데 있어 최소 18시간 이상이 필요하며, 이러한 분변성대장균 측정 방식은 하천 이용자들이 안전한 친수활동을 영위하는데 있어 적절한 수질 정보를 제공하지 못한다. 그러므로 분변성대장균을 예측하는 모델을 개발하고, 이를 이용하여 실시간 분변성대장균 정보를 생성하여 하천 이용자들에게 제공할 필요가 있다. 본 연구에서는 친수활동이 활발하게 이루어지는 곳 중 하나인 북한강의 대성리 지점에 대해 데이터 기반 모델을 이용하여 분변성대장균을 예측하였다. 데이터 기반 모델은 물리 기반 모델에서 필요한 지형데이터나 비점오염원 등의 초기 오염물의 양에 대한 데이터를 필요로 하지 않고, 대신 독립변수로 사용되는 기상 및 수질데이터를 필요로 한다. 이러한 기상 및 수질데이터는 기존 기상관측소, 수질관측소에서 매일 자동으로 측정되기 때문에 데이터 기반 모델은 물리 기반 모델에 비해 입력데이터를 구성하기가 쉽다는 장점을 지닌다. 이러한 데이터 기반 모델 중 분류 모델은 회귀 모델과 달리 분변성대장균 농도가 일정 수질기준 이상을 넘는지를 바로 예측할 수 있다. 본 연구에서는 분류 모델 중 높은 예측력을 가진다고 알려진 랜덤포레스트(random forest) 기법을 이용하여 분변성대장균 예측 모델을 개발하였다. 분변성대장균 예측 모델은 주어진 기상 및 수질 조건에 대해 분변성대장균이 200 CFU/100ml가 넘는지를 예측하였다. 예측된 분변성대장균이 기준을 넘는 경우를 2등급, 넘지 않는 경우를 1등급으로 명명하였다. 모델을 개발하기 위하여 북한강 대성리 인근 측정소에서 2010년부터 2015년까지 측정된 기상 및 수질데이터를 수집하였다. 수집한 데이터를 훈련 및 검증데이터로 샘플링하였으며, 이 때 샘플링한 데이터가 기존 데이터가 가지고 있던 등급별 비율을 유지하기 위하여 층화샘플링을 하였다. 본 연구에서는 샘플링에 의한 불확실성을 줄이기 위하여 랜덤하게 50번 샘플링된 각각의 훈련데이터에 대해 모델을 개발하였다. 50개의 모델의 검증 결과를 종합한 결과, 전체 예측률은 0.139로 나타났다.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1135-1148
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• 2018

Previous studies on reservoir operation have been assumed that the climate in the future would be similar to that in the past. However, in the presence of climate non-stationarity, Robust Optimization (RO) which finds the feasible solutions under broader uncertainty is necessary. RO improves the existing optimization method by adding a robust term to the objective function that controls the uncertainty inherent due to input data instability. This study proposed Robust-SDP that combines Stochastic Dynamic Programming (SDP) and RO to estimate dam operation rules while coping with climate non-stationarity. The future inflow series that reflect climate non-stationarity were synthetically generated. We then evaluated the capacity of the dam operation rules obtained from the past inflow series based on six evaluation indicators and two decision support schemes. Although Robust-SDP was successful in reducing the incidence of extreme water scarcity events under climate non-stationarity, there was a trade-off between the number of extreme water scarcity events and the water scarcity ratio. Thus, it is proposed that decision-makers choose their optimal rules in reference to the evaluation results and decision support illustrations.

• Journal of Korea Water Resources Association
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• v.52 no.2
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• pp.149-161
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• 2019

In this study, the effect of the fluid flow characteristics on the length distribution of the fracture elements composing the fracture network is analyzed numerically using the 3D fracture crack network model. The truncated power-law distribution is applied to generate the length distribution of the fracture elements and the simulations of fluid flow are carried out with the exponent ${\beta}_l$ from 1.0 to 6.0. As a result of simulations, when the exponent ${\beta}_l$ increases, the length distribution of the fracture elements gradually decreases, and the connectivity between the fracture elements affecting the permeability of the fracture network becomes weak. When we analyzed the distributions of flow rate calculated at each fracture element with the exponent ${\beta}_l$, the mean flow rate at ${\beta}_l=1.0$ was estimated to be about 447 times larger than that at ${\beta}_l=6.0$ and for the flow calculated at the outflow boundary of the fracture network, the case of ${\beta}_l=1.0$ was estimated to be 6,440 times larger than that of ${\beta}_l=6.0$.

• Geophysics and Geophysical Exploration
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• v.22 no.3
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• pp.149-159
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• 2019

Borehole elemental concentration logging, measuring neutron-induced gamma rays by inelastic scattering and neutron capture interactions between neutron and formation, delivers concentrations of the most common elements found in the minerals and fluids of subsurface formation. X-ray diffraction and X-ray fluorescence analysis from core samples are traditionally used to understand formation composition and mineralogy, but it represents only part of formations. Additionally, it is difficult to obtain elemental analysis over the whole intervals because of poor core recovery zones such as fractures or sand layers mainly responsible for groundwater flow. The development of borehole technique for in situ elemental analysis plays a key role in assessing subsurface environment. Although this technology has advanced consistently starting from conventional and unconventional resources evaluation, it has been considered as exclusive techniques of some major service company. As regards domestic research and development, it has still remained an unexplored field because of some barriers such as the deficiency of detailed information on tools and calibration facility for chemistry and mineralogy database. This article reviews the basic theory of spectroscopy measurements, system configuration, calibration facility, and current status. In addition, this article introduces the domestic researches and self-development status on borehole elemental concentration tools.

• Management & Information Systems Review
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• v.38 no.1
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• pp.63-81
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• 2019

In order to overcome the disadvantages of banner ad, pop-up ad, interstitial ad, which are existing web advertisement forms, native ad is actively utilized. Native advertising is considered to be a useful advertising technique in that it can reduce users' rejection and attract attention. However, in recent years, there have been a lot of fake news and fake contents that have turned articles or video contents into advertisements. The purpose of this study is to understand how firms can coordinate and control native advertisements in a rational way. For this analysis, we conducted a survey of 308 social media users using quota sampling method. As a result of the verification, it was found that the more negative the perception of the evaluation of the advertisement, the less the level of persuasion about the advertisement and the negative impact on the website where the advertisement is exposed. In addition, this study examined the influence of the negative stimulus factors on the qualitative performance of the firm. As a result, it was found that source non-expert had the highest effect on skepticism on ad. Also, platform overflow has a direct effect on the evaluation of the website as well as the negative evaluation of the advertisement. Moreover, this study provides concrete implications for the subdivision market by verifying the differences between the paths according to the level of website involvement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.106-117
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• 2021

In Korea, interest in truck platooning is increasing because most cargo transportation is done by road. Truck platooning is the operation of two or more trucks in a row to form one platoon, which can increase road capacity and improve fuel efficiency. In this study, to analyze the effect of truck platooning on traffic flow, scenarios were created according to traffic conditions and truck platooning operating conditions. In order to understand the effect of the truck platooning operating conditions, correlation analysis was conducted with the average travel speed, the number of lane change disturbance, and the number of disturbance in the entry/exit section. As a result, the number of trucks in the platoon, the spacing of trucks in the platoon, and the spacing between platoons were found to have an effect on the average speed and the number of lane change disturbance In addition, the truck platooning ratio was found to have a strong correlation with the average travel speed and the number of lane change disturbance regardless of the LOS.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.384-395
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• 2020

Breaking waves generated by wave shoaling in coastal areas have a close relationship with various physical phenomena in coastal regions, such as sediment transport, longshore currents, and shock wave pressure. Therefore, it is crucial to accurately predict breaker index such as breaking wave height and breaking depth, when designing coastal structures. Numerous scientific efforts have been made in the past by many researchers to identify and predict the breaking phenomenon. Representative studies on wave breaking provide many empirical formulas for the prediction of breaking index, mainly through hydraulic model experiments. However, the existing empirical formulas for breaking index determine the coefficients of the assumed equation through statistical analysis of data under the assumption of a specific equation. In this paper, we applied a representative linear-based supervised machine learning algorithms that show high predictive performance in various research fields related to regression or classification problems. Based on the used machine learning methods, a model for prediction of the breaking index is developed from previously published experimental data on the breaking wave, and a new linear equation for prediction of breaker index is presented from the trained model. The newly proposed breaker index formula showed similar predictive performance compared to the existing empirical formula, although it was a simple linear equation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.685-693
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• 2021

This study examined the fire risk of the region in Goyang City using the spatial information data of buildings. The economic damage by industry was assessed according to the probability of fire risk. The study area was confined to Goyang-si, Gyeonggi-do, and the same fire risk reduction rate was applied to each region for the convenience of analysis. The possibility of fire was derived based on the buildings' density and usage in the area by National GIS building-integrated information standard data. The calculation of economic damage by industry in Goyang City due to the fire risk was calculated by combining the Goyang-si industry-related model produced by matching with 30 industrial categories in Input-Output Statistics of Korea Bank and 20 industrial categories in the Goyang-si business survey and the possibility of fire. The basic scenario of production impossibility during six months and business loss due to fire was established and analyzed based on the supply model. The analysis showed that Ilsan-dong-gu, Ilsan-seo-gu, and Deokyang-gu suffered the most economic damage. The "electricity, gas, steam, and water business" showed the greatest loss by industry.