• Ecology and Resilient Infrastructure
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• v.3 no.1
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• pp.54-61
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• 2016

There are many pilot programs and projects to implement the water quality trading (WQT) policy. But actual trading is relatively rare. The main reason of the scarce applications of WQT policy is the difficulty in determining the equalities between the trading sites. The uncertainty of the impacts of the nonpoint sources pollutant discharges between up and downstream urban development areas also makes the implementation of the policy harder. The simulated results from the watershed modeling program will be used to calculate the point and nonpoint sources pollutants of the future urban development scenarios. The amount of suspended sediments resulting from the urban developments and rainfall intensities will be used to indicate the environmental impacts of the water body between upstream and downstream. The water quality impacts after development scenarios to the outlet of the watershed were transferred to the trading units between two sites. The recommended trading units can be used as a decision support system for policy makers and stakeholders to carry out better WQT practices.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.407-413
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• 1998

This study reviewed the recent studies for the climate change impact on water resource systems and applied one of the techniques to a real reservoir system - the Skagit hydropower system in U.S.A. The technique assumed that the climate change results in ±5% change in monthly average and/or standard deviation of the observed inflows for the Skagit system. For each case of the altered average and standard deviation, an optimal operating policy was derived using s SDP(Stochastic Dynamic Programming) model and compared with the operating policy for the non-climate change case. The results showed that the oparating policy of the Skagit system is more sensitive to the change in the streamflow average than that in the streamflow standard deviation. The derived operating policies were also simulated using the synthetic streamflow scenarios and their average annual gains were compared as a performance index. To choose the best operating policy among the derived policies, a Bayesian decision strategy was also presented with an example. Keywords : climate change, reservoir operating policy, stochastic dynamic programming, Bayesian decision theory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.24-31
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• 2018

As a system complexity increases and technology innovation progresses rapidly, leasing the equipment is considered as an important issue in many engineering areas. In practice, many engineering fields lease the equipment because it is an economical way to lease the equipment rather than to own the equipment. In addition, as the maintenance actions for the equipment are costly and need a specialist, the lessor is responsible for the maintenance actions in most leased contract. Hence, the lessor should establish the optimal maintenance strategy to minimize the maintenance cost. This paper proposes two periodic preventive maintenance policies for the leased equipment. The preventive maintenance action of policy 1 is performed with a periodic interval, in which their intervals are the same until the end of lease period. The other policy is to determine the periodic preventive maintenance interval minimizing total maintenance cost during the lease period. In addition, this paper presents two decision-making models to determine the preventive maintenance strategy for leased equipment based on the lessor's preference between the maintenance cost and the reliability at the end of lease period. The structural properties of the proposed decision-making model are investigated and algorithms to search the optimal maintenance policy that are satisfied by the lessor are provided. A numerical example is provided to illustrate the proposed model. The results show that a maintenance policy minimizing the maintenance cost is selected as a reasonable decision as the lease term becomes shorter. Moreover, the frequent preventive maintenance actions are performed when the minimal repair cost is higher than the preventive maintenance cost, resulting in higher maintenance cost.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.1
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• pp.58-65
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• 2019

The stability, reliability and efficiency of a smart ship are important issues as the interest in an autonomous ship has recently been high. An automatic collision avoidance system is an essential function of an autonomous ship. This system detects the possibility of collision and automatically takes avoidance actions in consideration of economy and safety. In order to construct an automatic collision avoidance system using reinforcement learning, in this work, the sequential decision problem of ship collision is mathematically formulated through a Markov Decision Process (MDP). A reinforcement learning environment is constructed based on the ship maneuvering equations, and then the three key components (state, action, and reward) of MDP are defined. The state uses parameters of the relationship between own-ship and target-ship, the action is the vertical distance away from the target course, and the reward is defined as a function considering safety and economics. In order to solve the sequential decision problem, the Deep Deterministic Policy Gradient (DDPG) algorithm which can express continuous action space and search an optimal action policy is utilized. The collision avoidance system is then tested assuming the $90^{\circ}$intersection encounter situation and yields a satisfactory result.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5B
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• pp.390-396
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• 2006

Policy-based Network Management(PBNM) in the Mobile Ad-hoc network(MANETs) requires additional, reliable and efficient mechanism over PBNM in wired network. Thus, it is important that the management system in MANETs should cluster the moving nodes and manage their movements in an effective manner. In this thesis, I propose a mechanism for the policy-based management in ad hoc networks in which I consider several methods to discover the Policy Decision Point(PDP), set the management area, and manage the movements of Policy Enforcement Point(PEP) nodes in the PBNM system. Moreover, COPS-PR is extended for the mechanism. Finally, I analyze and validate the results through simulations.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.73-82
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• 2000

This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

• Health Policy and Management
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• v.19 no.4
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• pp.98-120
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• 2009

The purpose of this study is to elicit preference for drug listing decision criteria and to estimate the ICER threshold in South Korea using the discrete choice experiment (DCE) method. To collect the data, a DCE survey was administered to a subject sample either educated in the principle concepts of pharmacoeconomics or were decision makers within that field. Subjects chose between alternative drug profiles differing in four attributes: ICER, uncertainty, budget impact and severity of disease. The orthogonal and balanced designs were determined through computer algorithm to take the optimal set of drug profiles. The survey employed 15 hypothetical choice sets. A random effect probit model was used to analyze the relative importance of attributes and the probabilities of a recommendation response. Parameter estimates from the models indicated that three attributes (ICER, Impact, Severity of disease) influenced respondents' choice significantly(p${\pm}$0.001). In addition, each parameter displayed an expected sign. The Lower the ICER, the higher the probability of choosing that alternative. Respondents also preferred low levels of uncertainty and smaller impact on health service budget. They were also more likely to choose drugs for serious diseases rather than mild or moderate ones. Uncertainty however is not statistically significant. The ICER threshold, at which the probability of a recommendation was 0.5, was 29,000,000 KW/QALY in expert group and 46,500,000 KW/QALY in industry group. We also found that those in our sample were willing to accept high ICER to get medication for severe diseases. This study demonstrates that the cost-effectiveness, budget impact and severity of disease are the main reimbursement decision criteria in South Korea, and that DCE can be a useful tool in analyzing the decision making process where a variety of factors are considered and prioritized.

• Journal of Family Resource Management and Policy Review
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• v.15 no.4
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• pp.169-188
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• 2011

The primary focus of this study was on the issues associated with family and economic decision-making, in particular for the elderlyhood which might have to (or could be) share the family resources. This study regarded willingness to consider applying for Reverse Mortgage as an economic decision-making. The data was collected by interviewing 320 persons (over age 55) living in metropolitan areas in 2008. We selected 227 cases to find the influence of family, having both spouse and adult-children. We have used a theory of Planned Behavior by Fishbein to analysis three research questions. The results are as follows : first, the results partially explain willingness to consider applying for reverse mortgage using Fishbein's theory. Second, several results indicated that economic decision-makings within the family are influenced by several factors relating to other family member's view. They means that some of Subjective Norm variables, of Attitude Behavior ones, and of Perceived Behavior Control ones. Third, the result shows men and women respond differently to consider to applying for that policy. Men are conscious of the other people, i.e., friends, relatives except close family members, and, on the other hand, women are mindful of close family members, i.e., adult children. Forth, the group who have lower income showed higher intentions to consider that policy, when they have adult-children. Fifth, according to age group, pre-elderly group are influenced by consent of adult-children, a level of education, and on the other hand, elderly group are influenced by the other people, i.e., friends, relatives, a level of education, and so on. These results meaned that these distinct characteristics should be considered to establish Income Security policy for the pre-elderly and the elderly.

• Journal of Korean Society for Quality Management
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• v.11 no.2
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• pp.2-9
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• 1983

As will be seen, this paper is tries that the research on the mathematical structure of Markov process and Markovian sequential decision process (the policy improvement iteration method,) moreover, that it analyze the logic and the characteristic of behavior of mathematical model of Markov process. Therefore firstly, it classify, on research of mathematical structure of Markov process, the forward equation and backward equation of Chapman-kolmogorov equation and of kolmogorov differential equation, and then have survey on logic of equation systems or on the question of uniqueness and existence of solution of the equation. Secondly, it classify, at the Markovian sequential decision process, the case of discrete time parameter and the continuous time parameter, and then it explore the logic system of characteristic of the behavior, the value determination operation and the policy improvement routine.

• Health Policy and Management
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• v.12 no.3
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• pp.99-111
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• 2002

This paper draws the determinants of National Health Expenditures(min) and collectivizes OECD countries which are positioned by same conditions using the decision tree analysis. Major findings are summarized as follows. We find that the power of influence of income level on NHE has been 58.35% in 1985, 65.37% in 1990, 66.90% in 1995, and 66.47% in 1997. The power of influence of public share in NHE has been on the increase during that period: 19.50% in 1985, 19.91% in 1990, 22.81% in 1995 and 26.88% in 1997. The two factors(income level, public share) tells for the most part of NHE: 77.85% in 1985, 85.28% in 1990, 89.71% in 1995, 93.35% in 1997. Our results support the hypothesis that NHE could be explained mostly by the income level and show that public share is negatively correlated with the growth of NHE.