• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.264-270
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• 1998

This research broadens the prime concern of nuclear power plant operations from safe performance to both economic and safe performance. First emergency diesel generator is identified as one of main contributors for the lost plant availability through the review of plants forced outage records. The framework of an integrated architecture for performing modern on-line condition for operational availability improvement is configured in this work. For the development of the comprehensive sensor networks for complex target systems, an integrated methodology incorporating a structural hierarchy, a functional hierarchy, and a fault-system matrix is formulated. The second part of our research is development of intelligent diagnosis and maintenance advisory system, which employs Bayesian Belief networks (BBNs) as a high level reasoning tool incorporating inherent uncertainty use in probabilistic inference. Our prototype diagnosis algorithms are represented explicitly through topological symbols and links between them in a causal direction. As new evidence from sensor network development is entered into the model especially, our advisory of system provides operational advice concerning both availability and safety, so that the operator is able to determine the likely modes, diagnose the system state, locate root causes, and take the most advantageous action. Thereby, this advice improves operational availability

• Bulletin of the Society of Naval Architects of Korea
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• v.20 no.1
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• pp.21-27
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• 1983

The mode superposition method(MSM) for the forced transverse vibration analysis of structures subject to Timoshenko beam analogy, which had originally been developed by Ormondroyd and McGoldrick, is reviewed to formulate it in more general form taking account of rotary inertia, dampings in separate terms of internal and external ones, and simultaneous action of exciting forces and moments. To investigate some general features of the method in practical utilizations, resonant maximum amplitudes of 4 high speed ships under concentrated sinusoidal excitation at the stern are calculated by both MSM and the finite difference method(FDM). For the FDM the hulls are discretized into 40 equal segments, and in utilization of MSM contributions of the first six modes are summed up to obtain responses up to the six-nodes resonant mode. The numerical results show that MSM gives slightly higher values, $4{\sim}10%$, than those by FDM. Since there is always uncertainty in the damping estimation of actual systems, influences of the damping magnitude on resonant amplitudes and a practical method to estimate modal damping coefficients are discussed.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.221-229
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• 2022

Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.17 no.2
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• pp.90-100
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• 2021

Molten corium-concrete interaction (MCCI) is one of the most important phenomena that can lead to the potential hazard of late containment failure due to basemat penetration during a severe accident. In this study, MCCI analytical models of the CORQUENCH code were prepared through verification calculations of several experiments, which had been performed using concrete types similar to those of the calandria vault floor in CANDU-6 plants. The behaviors of thermal-hydraulic variables related to MCCI phenomena were analyzed under the conditions of dry floor and water flooding during the severe accident stemming from a hypothetic station blackout. Uncertainty analyses on the ablation depth were also carried out. It was estimated that the concrete ablation was not interrupted due to the continuous MCCI process under the dry condition but was terminated within 24 hours under the water flooding condition. It was confirmed that the water flooding as a mitigating action was effective to achieve the quenching and thermal stabilization of the melt discharged from the calandria vessel, showing that the present models are capable of reasonably simulating MCCI phenomena in CANDU-6 plants. This study is expected to provide the technical bases to the accident management strategy during the late-phase severe accidents.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.672-680
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• 2003

A shopbot is a software agent whose goal is to maximize buyer´s satisfaction through automatically gathering the price and quality information of goods as well as the services from on-line sellers. In the response to shopbots´ activities, sellers on the Internet need the agents called pricebots that can help them maximize their own profits. In this paper we adopts Q-learning, one of the model-free reinforcement learning methods as a price-setting algorithm of pricebots. A Q-learned agent increases profitability and eliminates the cyclic price wars when compared with the agents using the myoptimal (myopically optimal) pricing strategy Q-teaming needs to select a sequence of state-action fairs for the convergence of Q-teaming. When the uniform random method in selecting state-action pairs is used, the number of accesses to the Q-tables to obtain the optimal Q-values is quite large. Therefore, it is not appropriate for universal on-line learning in a real world environment. This phenomenon occurs because the uniform random selection reflects the uncertainty of exploitation for the optimal policy. In this paper, we propose a Mixed Nonstationary Policy (MNP), which consists of both the auxiliary Markov process and the original Markov process. MNP tries to keep balance of exploration and exploitation in reinforcement learning. Our experiment results show that the Q-learning agent using MNP converges to the optimal Q-values about 2.6 time faster than the uniform random selection on the average.

• Health Policy and Management
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• v.9 no.4
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• pp.41-64
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• 1999

The major concern for this research is to discuss and to offer some solutions to bring the effectiveness of existing notifiable diseases reporting system over the physicians' attitudes of reporting, the actual condition of performance and the reasons of inertia in notifiable diseases reporting through examining the physicians of medical institutions in nationwide such as pediatrics, internal medicine and family medicine. The actual conditions of notifiable communicable diseases(NCD) reporting was surveyed by mail objectifying an internal medicine, pediatrics and family medicine in nationwide on the basis of stratified random sampling method divided into the classification of medical institutions and areas. As a result of survey. the rate of respondents showed 145 persons from physicians, 105 persons from hospitals. 120 persons from general hospitals, and 51 persons from tertiary hospitals. The total number of respondents were 421 and was rated 59.0 %. The analysis of collected survey went through a descriptive analysis primarily to grasp physicians' attitudes on the notifiable communicable diseases reporting, and then upon the dependent variables. Following are major findings obtained form the data analysis. 1. The results of a descriptive analysis on physicians' attitudes towards reporting NCD were as follows: First, the respondents who didn't know that yellow fever is reporting NCD were 11.0% of clinic, 10.5% of hospital. 5.0% of general hospital. 11.8% of tertiary hospital. and in case of hepatitis B, were 26.9% of clinic, 35.2% of hospital. 35.0% of general hospital. 23.5% of tertiary hospital. Second, The rate of physicians' knowledge on penalties of not reporting the NCD by their medical institution were 35.2% of clinic, 45.7% of hospital. 36.7% of general hospital. 62.7% of tertiary hospital. Third, among the no-reporting physicians in whole, the major reason of not reporting NCD were uncertainty of diagnosis(78.9%), no need to report(46.4%), no adequate actions from PHC(29.1%), no knowledge of the cases being notifiable ones in the order of their frequencies(30.4%), meddling from PHC(29.1%), concerning of patient's privacy(26.3%). 2. To analyze the characteristics related to the physicians' behaviors to report NCD, univariate and multiple logistic regression analyses were applied to the variables related to physician, 4 medical facility, PHC, and reporting system. The result were as follows: First, the result of the univariate analysis on physicians' attitude to report NCD and characteristics related to reporting in odds ratio was in the case of hospital. 3.4 times higher positive responses on physicians' attitude to report NCD came up as compared to the clinic. Second, the result of the univariate analysis on physicians' action of reporting NCD and characteristics related to reporting by the classification of medical institutions showed that the odds ratio of hospital was 2.3 times, the odds ratio of general hospital was 2.0 times, the odds ratio of tertiary was 6.8 times significantly higher than clinic. And the medical institution with significantly higher positive attitudes rate by multiple logistic regression analysis was hospital that rated 2.5 times significantly higher than clinic. Also in the PHC related characteristics of reporting, the rate of action in reporting NCD was significantly higher in medical institution that were endowed with the good condition of reporting. In multiple logistic regression analysis, the medical institution that has a good conditions of reporting showed a significantly higher positive rate on the action of reporting than the others.

• Journal of Korean Academy of Nursing
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• v.27 no.3
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• pp.614-626
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• 1997

The main purposes of the study were to develop and test a model which explains the dynamic relationship among factors reported as affecting to the quality of life of individuals with rheumatoid arthritis and to examine the relationship between self-help response and quaility of life. Data for the study were collected from March 1996 to December 1996 from 153 female patients who regularly visited a clinic for people with rheumatism. The patients were introduced to the investigators by nurses who worked at that clinic, and then the investigator interviewed the patients for 30 to 40 minutes to collect the data. Instruments used in the study were modified self-report questionaires from the ones which were already developed in previous studies or from related literature. Data analysis were performed using LISREL(Lineal Structural Relations) 8 program to test whether the proposed hypothesized model fit the collected data. To test the fitablity of the hypothesized model both a general fit measure and a detailed fit measure were used. Based on the test results from the various fit measures, the hypothesized model was found to be well suited to the real data. As characteristics related to illness becomes severe, the feasibility for these characteristics leading to the perception of uncertainty about the illness tend to increase, but, the direct effects from the illness characteristics(such as level of physical symptoms, sense of social-psychologic change, limitations of action) as they are related to the other intrinsic variables (self-efficacy or self-help behavior and quality of life), were found to be not significant. It was found that uncertainty had a direct effect on self-efficacy but did not have a direct effect on self-help behavior or quality of life. Also, it is noted that self-efficacy had a positive effect on self-help behavior and quality of life and there was a bilateral relationship between self-efficacy and self-help behavior. Lastly, the hypothesis proposed from the theoretical model in this study was supported basis of the results that self-help behavior provides both direct and positive effects to quality of life. Particularity, since a bilateral relationship was also found between self-help behavior and quality of life in the modified model, as self-help behavior increased, so did quality of life. And, reversely, as quality of life increased, so did self-help behavior. In conclusion, the results of this study suggest that focusing on both acquirement and reinforcement of adjustment factors or self-help behavior is more efficient than focusing on the characteristics of illness in establishing the stategies for improving quality of life of individuals with rheumatoid arthritis.

• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.732-753
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• 2017

Recently, when evaluating the technology values in the fields of biotechnology, pharmaceuticals and medicine, we have needed more to estimate those values in consideration of the period and cost for the commercialization to be put into in future. The existing discounted cash flow (DCF) method has limitations in that it can not consider consecutive investment or does not reflect the probabilistic property of commercialized input cost of technology-applied products. However, since the value of technology and investment should be considered as opportunity value and the information of decision-making for resource allocation should be taken into account, it is regarded desirable to apply the concept of real options, and in order to reflect the characteristics of business model for the target technology into the concept of volatility in terms of stock price which we usually apply to in evaluation of a firm's value, we need to consider 'the continuity of stock price (relatively minor change)' and 'positive condition'. Thus, as discussed in a lot of literature, it is necessary to investigate the relationship among volatility, underlying asset values, and cost of commercialization in the Black-Scholes model for estimating the technology value based on real options. This study is expected to provide more elaborated real options model, by mathematically deriving whether the ratio of the present value of the underlying asset to the present value of the commercialization cost, which reflects the uncertainty in the option pricing model (OPM), is divided into the "no action taken" (NAT) area under certain threshold conditions or not, and also presenting the estimation logic for option values according to the observation variables (or input values).

• Economic and Environmental Geology
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• v.41 no.5
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• pp.551-562
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• 2008

Option pricing model in finance has been applied to price non-financial options, called real options. The real option valuation method is ideally suited to irreversible decision making under uncertainty, including the need to determine the optimal time to act and even change between alternative courses of action as information is collected. Therefore, the real option valuation method is expected to provide a superior and less subjective approach to determining optimal strategies for water resources supply projects, which have been reported to have huge risks due to uncertainties, and investors and policy makers need to build an optimal strategy - when and if to invest - with uncertainties and managerial flexibilities considered.

• STI Policy Review
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• v.6 no.2
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• pp.54-86
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• 2015

The study examines the U.S. Small Business Innovation Research (SBIR) program, with a focus on the recent Reauthorization, and compares, in the political context, the U.S. and East Asian countries-Japan, Korea and Taiwan-that adopted the U.S. SBIR program. For the systematic analysis and cross-country comparison, the study employs Kingdon (2003)'s framework-his political theory and Garbage Can Model-to identify political participants and processes underlying the SBIR Reauthorization and to analyze the differences in problem, policy, and politics streams between the U.S. and East Asian countries. For the cross-country comparison, specifically, the study uses various data sources such as OECD, Global Entrepreneurship Monitor, Hofstede's Cultural Dimensions, and World Value Survey. Based on the analysis outcomes, implications of U.S. practices on East Asian countries are extracted as follows. East Asian countries tend to: Have higher entrepreneurial aspiration while lower entrepreneurial activity and attitude than the U.S.; bear higher long term orientation and uncertainty avoidance while lower individualism than the U.S.; and have greater expectations of technology development and higher confidence in political parties while participating less in political action than the U.S. Drawing on the differences, the following policy recommendations are suggested. East Asian countries should: Improve entrepreneurs' access to resources (in particular, financial resource) in order to link their high entrepreneurial aspiration to actual entrepreneurial activities; cultivate failure-tolerating culture and risk-taking entrepreneurs, for instance, by providing a second chance to SBIR-participating businesses that failed to materialize their innovative ideas; and leverage their high expectations of new technology in order to take bold actions regarding their SBIR programs, and update the programs by drawing out constructive dialogues between SBIR stakeholders.