• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.695-713
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• 2009

This study investigates the determinants of municipal water prices and costs in Korea. A panel data set of 164 municipalities for the period 2000~2007 is used for the study. Both random and fixed effect models with an appropriate set of instruments are applied to the data. Substantial differences in prices and costs among municipalities are observed. The study finds that prices and costs increase if the leakage rate is high, the quality of primary water is bad, and the municipality has to purchase primary water from K-water which is the single creation and management corporation of water resources facilities in Korea. Prices and costs decline if the size of consumer is large, the proportion of paying consumer is high, and the amount of subsidy from the central government is large.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.678-682
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• 2012

본 연구는 한국건설기술연구원의 주요사업인 "산지하천 유역의 홍수예측을 위한 수문조사(2011~2015년)"의 Test-bed 유역중의 하나인 설마천 유역(경기도 파주시 적성면)을 운영하면서 신뢰성 있는 수문자료를 지속적으로 획득함과 동시에 산지하천 유역의 홍수량 예측과 재해방지 설계기법을 개선하고 수문정보를 제공하는데 있다(Test-bed 유역중의 또 하나인 차탄천 유역은 2011년 수문관측 기반구축 완성). 이를 위하여 2011년에도 지속적인 수문조사를 하였으며, 수문자료의 품질 향상을 위한 관측기기의 유지관리와 수집된 자료의 처리절차를 통하여 신뢰성 있는 수문자료를 생성하고, 이들 자료를 바탕으로 유역의 수문특성을 분석하였다. 또한 홍수량 예측과 재해방지 설계기법 개선을 위해서는 관련 기술조사, 평가와 취약 설계인자를 도출하였으며, 정량화를 위한 시험 및 조사방법을 결정하는 과정을 진행하고 있다. 설마천-차탄천 수문정보시스템(http://seolmacheon.kict.re.kr)은 Test-bed 유역(설마천 유역 이외에 차탄천 유역 포함)에서 생성되는 수문자료를 수집, 저장, 공유하는 기능을 포함하고, 홍수예측 모형(집중형 모형)과 강우레이더 자료(RDAPS 자료)를 결합한 산지하천의 홍수예측을 모의할 수 있는 기능을 추가하였으며, 향후 모의의 정도를 개선하고자 다른 모형과 다른 강우레이더 자료 도입을 목표로 진행할 예정이다. 그리고 Test-bed 유역을 기반으로 한 홍수량 예측 모형의 적용성 평가를 통해 중 소규모 산지하천 유역에 적합한 실시간 홍수예보 시스템 개발과 유역 수문조사 지침서 작성을 통해 가이드를 제시하고자 한다. 2011년 설마천 유역에서 생성된 자료로는 6개 우량관측소의 우량자료, 2개 수위관측소의 하천수위 및 지하수위, 유량측정성과 등이 있으며, 이로부터 산정된 유역평균우량과 유량자료 등이 있다. 확정된 강우-유출자료를 이용하여 강우의 호우사상 분석(강우강도, 지속기간), 강우의 지속기간별 최대강우량, 강우의 시 공간 분포 특성 분석, 월별 유출 및 주요 호우사상의 유출특성 분석 등 기본적인 강우-유출 특성을 분석하였다. 그리고, 유량측정성과의 불확실도 분석을 통하여 측정한 유량자료의 정확도를 제고하였다. 설마천 유역에서 축적된 수문자료는 자료의 공유를 통하여 자료의 검증을 확보함과 동시에 연구성과가 수자원 개발 분야에 활용되기 위해서는 지속적이고 안정적인 자료확보와 수문관측 기술개발을 위한 노력과 투자가 더욱더 필요한 상황이다.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.65-72
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• 2020

The purpose of this study is to analyze the adequacy of product qualification criteria through Monte-Carlo simulation and association rule analysis. We first surveyed the similar procurement systems, then we simulated the bid situation that randomly generated several vendors participated in a bid, and they obtained the score according to the product qualification criteria's judgement area. Then, the company with the highest score will win the bid, and further analysis was performed in terms of performance indicator and satisfaction ratio. The results of this study can be summarized as follows; Although the items related to the credibility accounted for the largest number items, it did not affect the actual bid results. It was analyzed that it is desirable to increase the allocation points in the area of business status and technical capability review than the current one.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.517-522
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• 2021

In this study, the causes of damage to the concrete sleepers in a ballast track with under sleeper pads attached to the base of the sleepers installed in the sharp curved track(R=180m) of the urban railway bridge were analyzed. The damage types of concrete sleepers were investigated, and the correlation with track irregularity was reviewed. Also, stress generated in the concrete sleeper was reviewed through structural analysis. As a result, most of the cracks of the sleepers occurred in the section with severe track irregularity. In addition, as a result of the analysis, the stress generated in the track components and the sleepers was found to be reduce in the fastening system using the 4-anchor.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.147-157
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• 2022

Recently, many studies have been conducted to analyze traffic or object recognition that classifies vehicles through artificial intelligence-based prediction models using CCTV (Closed Circuit TeleVision)or drone images. In order to develop an object recognition deep learning model for accurate traffic estimation, systematic data construction is required, and related standardized guidelines are insufficient. In this study, previous studies were analyzed to derive guidelines for establishing artificial intelligence-based training data for traffic estimation using drone images, and business reports or training data for artificial intelligence and quality management guidelines were referenced. The guidelines for data construction are divided into data acquisition, preprocessing, and validation, and guidelines for notice and evaluation index for each item are presented. The guidelines for data construction aims to provide assistance in the development of a robust and generalized artificial intelligence model in analyzing the estimation of road traffic based on drone image artificial intelligence.

• Composites Research
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• v.21 no.1
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• pp.22-29
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• 2008

This paper presents the evaluation of crashworthiness and rollover characteristics of low-floor bus vehicles made of aluminum honeycomb sandwich composites with glass-fabric epoxy laminate facesheets. Crashworthiness and rollover analysis of low-floor bus was carried out using explicit finite element analysis code LS-DYNA3D with the lapse of time. Material testing was conducted to determine the input parameters for the composite laminate facesheet model, and the effective equivalent damage model for the orthotropic honeycomb core material. The crash conditions of low-floor bus were frontal accident with speed of 60km/h. Rollover analysis were conducted according to the safety rules of European standard (ECE-R66). The results showed that the survival space for driver and passengers was secured against frontal crashworthiness and rollover of low-floor bus. Also, The modified Chang-Chang failure criterion is recommended to predict the failure mode of composite structures for crashworthiness and rollover analysis.

• Composites Research
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• v.20 no.4
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• pp.42-50
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• 2007

This paper describes the results of experiments and numerical simulation studies on the low-velocity impact damage of two different sandwich composite panels for application to bodyshell and floor structure of the BIMODAL tram vehicle. Square test samples of 100mm sides were subjected to low-velocity impact loading using an instrumented testing machine at four impact energy levels. Part of this work presented is focused on the finite element analysis of low-velocity impact response onto a sandwich composite panels. It is based on the application of explicit finite element (FE) analysis codes LS-DYNA 3D to study the impact response of sandwich structures under low-velocity impact conditions. Material testing was conducted to determine the input parameters for the metallic and composite material model, and the effective equivalent damage model for the orthotropic honeycomb materials. Numerical and experimental results showed a good agreement for damage area and the depth of indentation of sandwich composite panels created by the impact loading.

• Convergence Security Journal
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• v.23 no.2
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• pp.55-66
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• 2023

Recently, there is an increasing movement to increase the value of AI learning data and to secure high-quality data based on previous research on AI learning data in all areas of society. Therefore, quality management is very important in construction projects to secure high-quality data. In this paper, quality management to secure high-quality data when building AI learning data and improvement plans for each construction process are presented. In particular, more than 80% of the data quality of unstructured data built for AI learning is determined during the construction process. In this paper, we performed quality inspection of image/video data. In addition, we identified inspection procedures and problem elements that occurred in the construction phases of acquisition, data cleaning, labeling, and models, and suggested ways to secure high-quality data by solving them. Through this, it is expected that it will be an alternative to overcome the quality deviation of data for research groups and operators participating in the construction of AI learning data.

• Convergence Security Journal
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• v.23 no.2
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• pp.95-102
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• 2023

The purpose of this paper was to confirm the operational level of the military department of universities, which plays a key role in the officer training process, through empirical research and confirm meaningful results for improvement. There are 11 university military departments operated through the Army, agreements, and semi-agreement, and the Data Envelopment Analysis (DEA) was applied from the perspective of resource input and performance for each university's military department operation to analyze relative efficiency and confirm specific directions for improvement. As a result of operational efficiency analysis, 6 DMUs (Decsision Making Unit) were found to be efficient in the BCC model out of 11 DMUs, and the evaluation results could be confirmed through classification of efficient and inefficient groups through data capture analysis. This paper may be of practical value in that it checks the efficiency of the comparative university military departments and confirms specific information for development through the DEA-Additive model that reflects several evaluation factors at once. Through this, the operators of each university's military department are admitted.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.