• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.3
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• pp.331-337
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• 2018

The decommissioning of nuclear power plants is generally executed in five steps, including preparation, decontamination, cutting/demolition, waste disposal and environmental restoration. So, for efficient decommissioning of nuclear power plants, worker safety, effects compared to cost, minimization of waste, possibility of reuse, etc., shall be considered. Worker safety and measurement technology shall be secured to exert optimal efficiency of nuclear power plant decommissioning work, for which accurate measurement technology for systems and devices is necessary. Typical In-Situ methods for decommissioning of nuclear plants are CZT, Gamma Camera and ISOCS. This study used ISOCS, which can be applied during the decommissioning of a nuclear power plant site without collecting representative samples, to take measurements of the S/G Water Chamber. To validate the measurement values, Microshield and the GEANT4 code was used as the actual method were used for modeling, respectively. The comparison showed a difference of $1.0{\times}10^1Bq$, which indicates that it will be possible to reduce errors due to the influence of radiation in the natural environment and the precision of modeling. Based on the research results of this paper, accuracy and reliability of measurement values will be analyzed and the applicability of the direct measurement method during the decommissioning of NPPs will be assessed.

• Journal of the Korea Organic Resources Recycling Association
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• v.22 no.1
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• pp.27-34
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• 2014

demand for a low-cost treatment technology is high because the sewage sludge has an 80% or higher water content and a high energy consumption cost. This study apply the thermal hydrolysis reaction that consumes a small amount of energy for sludge treatment. The purpose of this study is to quantify the viscosity of sewage sludge according to reaction temperature. we measured continuously the torque of dewatered sludge by the reaction temperature. As the reaction temperature increased, the dewatered sludge is thermal hydrolysis under a high temperature and pressure. Therefore, the bond water in the sludge cells comes out as free water, which changes the dewatered sludge from a solid phase to slurry of a liquid phase. The results of the viscosity measurements according to the reaction temperature showed that the viscosity was very high at $270,180kg/m{\cdot}sec$ at a temperature of 293K, but rapidly decreased with increases in the reaction temperature to $12kg/m{\cdot}sec$ at a temperature of 400K and to $4kg/m{\cdot}sec$ at a temperature of 460K or higher, similar to the changes in the viscosity of water. And we was obtained the viscosity function of boundary condition for the optimal design of thermal hydrolysis reactor by numerical modeling based on the this results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2809-2817
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• 2010

The scholarly concern of train industry has been improved, since country focuses on this field. Especially, train maintenance facility has been studied for construction, because the facility is important to inspect the train that transports passenger and cargo. Various operation plans and criteria are considered to build train maintenance facility. In this paper, the decision making of train maintenance facility for construction is studied and analyzed with simulation, because mathematical theory is restricted to consider various operation plans and criteria. Through simulation, we analyze warm-up after selecting dependent factors, and extract data. The data is used to select a alternative in this problem, Multiple Attribute Decision Making(MADM). Previous study is difficult, complex and subjective for decision making. However, entropy measurement we used help decision maker for decision making, easily, simply, and objectively. This method can have decision maker choose the best alternative in case the train maintenance facility construction is fast revitalized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.740-748
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• 2016

IT and communication technologies has contributed significantly to the convenience of passengers and the financial management of stations in accordance with the task automation in the field of the urban railway system. The foundation of the above development is based on the large amounts of data from various sensors installed in railways, trains, and stations. In particular, the sensor network that is installed in the station and train has played an important role in the railway information system. The performance of AP is affected by the number of APs and their locations installed in the station. In the installation of APs in stations, the intensity of the radio wave of the AP on its underlying position is considered to determine the number and position of APs. This paper proposes a method to estimate the number of APs and their position based on the structure of the underlying station and implemented a simulator to simulate the performance of the proposed method. The implemented simulator was applied to the decision of AP installation at Busan Seomyeon station to evaluate its performance.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.109-123
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• 2004

Corporate financial distress and bankruptcy prediction is one of the major application areas of artificial neural networks (ANNs) in finance and management. ANNs have showed high prediction performance in this area, but sometimes are confronted with inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large because training the large data set needs much processing time and additional costs of collecting data. Instance selection is one of popular methods for dimensionality reduction and is directly related to data reduction. Although some researchers have addressed the need for instance selection in instance-based learning algorithms, there is little research on instance selection for ANN. This study proposes a genetic algorithm (GA) approach to instance selection in ANN for bankruptcy prediction. In this study, we use ANN supported by the GA to optimize the connection weights between layers and select relevant instances. It is expected that the globally evolved weights mitigate the well-known limitations of gradient descent algorithm of backpropagation algorithm. In addition, genetically selected instances will shorten the learning time and enhance prediction performance. This study will compare the proposed model with other major data mining techniques. Experimental results show that the GA approach is a promising method for instance selection in ANN.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.565-572
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• 2020

This study developed a software platform using machine learning of artificial intelligence to optimize the distillation column system. The distillation column is representative and core process in the petrochemical industry. Process stabilization is difficult due to various operating conditions and continuous process characteristics, and differences in process efficiency occur depending on operator skill. The process control based on the theoretical simulation was used to overcome this problem, but it has a limitation which it can't apply to complex processes and real-time systems. This study aims to develop an empirical simulation model based on machine learning and to suggest an optimal process operation method. The development of empirical simulations involves collecting big data from the actual process, feature extraction through data mining, and representative algorithm for the chemical process. Finally, the platform for the distillation column was developed with verification through a developed model and field tests. Through the developed platform, it is possible to predict the operating parameters and provided optimal operating conditions to achieve efficient process control. This study is the basic study applying the artificial intelligence machine learning technique for the chemical process. After application on a wide variety of processes and it can be utilized to the cornerstone of the smart factory of the industry 4.0.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.806-813
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• 2012

In a cloud computing environment, various solutions were introduced to provide the service to users such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS) and Desktop as a Service (DaaS). Nowadays, Mobile as a Service (MaaS) to provide the mobility in a cloud environment. In other words, users must have access to data and applications even when they are moving. Thus, to support the mobility to a mobile Thin-Client is the key factor. Related works to support the mobility for mobile devices were Mobile IPv6 and Proxy Mobile IPv6 which showed performance drawbacks such as packet loss during hand-over which could be very critical when collaborating with cloud computing environment. The proposed model in this paper deploys middleware and replica servers to support the data transmission among cloud and PMIPv6 domain. It supports efficient mobility during high-speed movement as well as high-density of mobile nodes in local mobility anchor. In this paper, through performance evaluation, the proposed scheme shows the cost comparison between previous PMIPv6 and verifies its significant efficiency.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.65-70
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• 2013

In many cases, operation of regional trunk lines is not profitable to railway operators. Nevertheless, railway operators are under pressure to manage regional trunk lines running under deficits, to better serve public interests. Given this situation, railway operators need to optimize assets by adjusting train schedules or changing the number of trains running. When railway operators judge the operation of a regional trunk line, the B/C ratio is generally used as a management index. This ratio is not considered part of strategic operational policy over the long term, and excessively influenced by the aspects of supply and demand over the short term. Accordingly, this study focused on indices that might be used to prevent worsening deficits and provide long term strategic operation policies, main indices to better measure economic situations, and auxiliary indices to supplement the main index. The main indices were measured in conventional ways to target experts and employees. This study presents quantitative standards, which are intended to be used to create itemized criteria through an Analytic Hierarchy Process, for better decision-making.

• Journal of Korean Society of Transportation
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• v.10 no.1
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• pp.55-62
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• 1992

교통수요는 교통정책 및 교통시설 계획의 수립 및 평가에 중요한 영향을 미치게 되므로 교통수요의 예측은 교통연구에서 중요한 부문을 차지하고 있다. 도로밑에 설치된 전자차량감지기(Electronic Vehicle Detector)로부터 자동 수집된 링크 교통량 자료(Traffic Counts)를 주요 입력자료로 이용하여 계획지역의 기종점 통행표(Origin Destination Trip Matrix)를 작성할 수 있는 기법 들이 최근 수년동안 많이 발달하게 되었다. 이러한 새로운 기법들은 가구조사(Home Inteview), 노변면접조사(Road-Side Interview)등을 토하여 조사된 자료를 기초로하는 전통적은 4단계 교통수요추정방법(Conventional 4-Stage Estimation Method)-통행발생(Generation), 통행분포(Distribution), 수단선택(Modal Split), 교통배분(Assignment)-과 비교하여 첫째로 정확도가 높은 링크 교통량 자료를 별도의 조사를 거치지 않고서도 수집이 가능하기 때문에 조사비용이 거의 들지 않아도 되어 경제적이고, 둘째로 전통적인 수요예측방법들에서 요구되어지는 복잡한 모형수립 및 계수조정(Parameter Calibration)이 필요하지 않아 간편하고 셋째로 오래전에 작성된 기종점 통행표를 단순히 링크 교통량 자료만을 이용하여 쉽게 보완할 수 있어 지속적인 자료의 축적(Data Age-ing)이 가능하며 더 나아 가서 소위 연속적인 교통 계획 및 교통시설관리(Continuous Transport Planning and Management)를 가능케 하는 등의 여러 장점 때문에 많은 주목을 받아 오고 최근 몇 년이 꾸준히 실무에 유용하게 적용이 되고 있는 실정이다. 본 연구는 링크 교통량자료를 이용하여 기종점 통행표를 작성하기 위하여 개발된 기존의 여러 기법들 가운데 특히 용량제약조건(Capacity-Restrained Condition)하에서 기존의 방법들을 상호 검토한 후 Wardrop의 교통망 평형원칙(Wardrop's First Network Equilibrium Principle)을 만족하는 새로운 추정기법을 제의하고 이의 시험결과를 논의하는 것을 주요내용으로 한다. 링크 교통량 자료를 이용하여 기종점 통행표를 작성하는 기법들의 근본 목표는 조사된 링크 교통량(Ob-served Traffic Counts)에 가장 근접한 교통망 통행 배정 링크 교통량(Assigned Link Volumes)을 재현(Re-producing)할 수 있는 기종점 통행표들 중에서 최적의 기종점 통행표를 발견하는 것이다. 따라서 교통망에서 통행자의 여행 경로 배정을 가장 잘 반영할 수 있는 현실적인(Realistic) 교통망 통행 배정 모형(Net-work Traffic Assignment Model)의 선택은 중요한 요소가 되며 특히 교통망에 교통체증(Traffic Conges-tion)이 심할 경우 교통망 통행자 평형조건(Network Traffic Equilibrium Condition)을 고려하기 위한 특별한 처리가 요구되어진다. 본 연구는 Whllumsen(Hall, Van Vliet and Willumsen, 1980)에 의하여 개발된 ME2(Maximum Entropy Matrix Estimation)기법에서 반복식 추정방법(Sequential Estimation Method)을 사용할 경우 Wardrop의 평형조건을 만족하는 기종점 통행표를 구할 수 없다는 단점을 극복하기 위한 방안으로서 엔트로피 극대화문제와 교통망 평형 조건(Entropy Maximisation and Network Equilibrium Condition)의 두 문제를 동시에 해결할 수 있는 새로운 수식모형과 이를 풀기 위한 알고리즘(Simultaneous Solution Algorithm)을 제의하였다. 제의된 수식모형과 알고리즘을 예제 교통망(Example Network)을 이용한 시험하고 그 결과를 ME2 의 반복식 추정 방법으로부터 구한 기종점 통행표와 비교 검토하였다.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.73-81
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• 2003

The Government presented improvement plans such as "Traffic Accident Frequent Point" and "Hazardous Roads" to reduce traffic accidents on the increase after 1980s. In case of the hazardous roads, they are expressed by grades which are marked by geometric elements such as width, radius, grade. sight distance. and other environmental factors. As each business for improving roads goes by only focusing on improvement of geometric elements, excessive expense can be invested too much nowadays causing economical waste. Therefore, as improvement plans approached by economic access are needed, this paper shows the cost-effective improvement of the business to keep safety related to traffic accident and economical waste. The hazardous roads which authorized by Gwang-ju National Road Preservation Office of Construction and Transportation Ministry in 1995 for business for improvement of roads, were investigated before 1999. First of all, estimating traffic accident models are presented by using existed data statistically. The models help to maximize traffic accident decrease through control of the presented factor. Secondly, optimum construction cost of improvement is presented to prevent overcapitalization. However, this paper is limited because it was difficult to sort the data with various areas and to approach various ways.