• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.11a
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• pp.137-137
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• 2007

• 한국지구물리탐사학회:학술대회논문집
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• 2009.05a
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• pp.101-118
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• 2009

In order to invest in overseas mineral projects, it is necessary to have a ability of technical and financial evaluation. Reserve estimation is the most important for mineral appraisal. Geostatistical evaluation of tonnage and grade promises more accurate reserve estimation than traditional methods such as polygon, inverse distance method and so on even if it has some uncertainty. Selection of a mining method and a mineral processing is also important because capex and opcosts of a mineral project is due to the selection. Mineral project is usually evaluated financially using NPV and IRR which are calculated through DCF(Discount Cash Flow). Uncertainty of a mineral project is analyzed statistically using sensitivity analysis and montecarlo simulation.

• Journal of Technology Innovation
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• v.11 no.1
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• pp.177-193
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• 2003

This paper examines empirically if the increase of funding uncertainty in government supported R&D institutes(GSRIs) in Korean cause managers to use more effective management control practices. Recently government introduced a new government R&D budget management system, based on competition, named PBS(Project Base System). Government requires GSRIs to be self-supporting and compete for funding from government. The introduction of new budget management system named PBS, has resulted in the increase of funding uncertainty in GSRIs. According to institutional theory, government organizations gain legitimacy by conforming to external expectations regarding management control practices, In contrast, contingency theory proposes that management control practices are driven by the fit between the technical features of the environment and the management control practices. The contingency literature provides that one external factor expected to motivate government managers to use more efficient control practices is the presence of competition and funding uncertainty. This paper use both theoretical perspective to develop hypotheses and examine the influence of funding environment on management control practices. Results show that the more institutionalized environment, the more managers in GSRIs rely on bureaucratic mode of control for conforming to external requirements, and the greater the funding uncertainty, the more managers use results and personal modes of control to improve research team performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4809-4818
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• 2022

The decommissioning project of a nuclear facility is a large-scale process that is expected to take about 15 years or longer. The range of risks to be considered is large and complex, then, it is expected that various risks will arise in decision-making by area during the project. Therefore, in this study, the risk family derived from the Decommissioning Risk Management (DRiMa) project was reconstructed into a decommissioning project risk profile suitable for the Kori Unit 1. Two criteria of uncertainty and importance are considered in order to prioritize the selected 26 risks of decommissioning project. The uncertainty is scored according to the relevant laws and decommissioning plan preparation guidelines, and the project importance is scored according to the degree to which it primarily affects the triple constraints of the project. The results of risks are divided into high, medium, and low. Among them, 10 risks are identified as medium level and 16 risks are identified as low level. 10 risks, which are medium levels, are classified in five categories: End state of decommissioning project, Management of waste and materials, Decommissioning strategy and technology, Legal and regulatory framework, and Safety. This study is a preliminary assessment of the risk of the decommissioning project that could be considered in the preparation stage. Therefore, we expect that the project risks considered in this study can be used as an initial data for reevaluation by reflecting the detail project progress in future studies.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.39-60
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• 1995

In this paper, an integration of stochastic dynamic programming (SDP), integer goal programming (IGP) and analytic hierarchy process (AHP) is proposed to handle multiobjective-multicriteria sequential decision making problems under uncertainty inherent in R & D investment planning. SDP has its capability to handle problems which are sequential and stochastic. In the SDP model, the probabilities of the funding levels in any time period are generated using a subjective model which employs functional relationships among interrelated parameters, scenarios of future budget availability and subjective inputs elicited from a group of decision makers. The SDP model primarily yields an optimal investment planning policy considering the possibility that actual funding received may be less than anticipated one and thus the projects being selected under the anticipated budget would be interrupted. IGP is used to handle the multiobjective issues such as tradoff between economic benefit and technology accumulation level. Other managerial concerns related to the determination of the optimal project portifolio within each stage of the SDP model. including project selection, project scheduling and annual budget allocation are also determined by the IGP. AHP is proposed for generating scenario-based transformation probabilities under budgetary uncertainty and for quantifying the environmental risk to be considered.

• Korean Management Science Review
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• v.31 no.3
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• pp.95-111
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• 2014

It is essential to carry out an economic analysis on public water supply projects so that policy makers and water enterprises are aware of the actual value of the project. However, many popular approaches based on discounted cash flow analysis do not capture the uncertainties inherent in cash flow. In order to analyze the economic values of the water supply project of local governments, we utilize real option model, which considers uncertainty in future water price behavior and captures the value of real life flexibility. The real option model is designed to incorporate the option to expand and abandon, and it is applied to a local government case. Furthermore, we assess the project by exploring Luehrman's option space to accommodate the more efficient decision making. The results show that substantial amount of potential value is included in the public water supply service, and the overall value is greater than the value obtained from the discounted cash flow model.

• Journal of the military operations research society of Korea
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• v.34 no.3
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• pp.107-116
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• 2008

This paper deals with modelling and introducing of the project portfolio construction and evaluation problem under uncertainty. The common way in industry of managing project portfolio is construction of initial portfolio considering uncertainties which exist inside and outside of portfolio, and periodic revision of portfolio due to the deviation from plans. In this paper, we introduce algorithm which reflecting the industrial common practice of initial planning and periodic revision. With this simulation method, probabilistic distribution of portfolio's performance in consideration can be found.

• Korean Journal of Child Studies
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• v.36 no.3
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• pp.195-213
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• 2015

This study aims to uncover what kinds of difficulties preschool teachers are now confronted with when they begin to implement project based learning with young children, in order to develop contents for teacher education programs. From July 2012 to February, 2013, 9 teachers participated in implementing projects in preschool classrooms. For data generation and interpretation, observations of class projects, tape-recordings of teacher conferences, and interviews with the teachers were made. The findings were as follows: teachers' uncertainty regarding project itself, teachers themselves, child competence, and its sustainableness were the most critical obstacle to hinder the teachers in implementing self directed projects with young children. The results imply that the teachers' belief in child competence in doing projects is of great significance; their view that it is very difficult for them to do projects without viewing young children a co-constructor of knowledge. Therefore, the key element in developing contents for teacher education programs should include a richer understanding of young children' competence.

• Nuclear Engineering and Technology
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• v.42 no.6
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• pp.690-703
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• 2010

Sampling based uncertainty analysis was carried out to quantify uncertainty in predictions of best estimate code RELAP5/MOD3.2 for a thermal hydraulic test (10% hot leg break LOCA) performed in the Large Scale Test Facility (LSTF) as a part of an IAEA coordinated research project. The nodalisation of the test facility was qualified for both steady state and transient level by systematically applying the procedures led by uncertainty methodology based on accuracy extrapolation (UMAE); uncertainty analysis was carried out using the Latin hypercube sampling (LHS) method to evaluate uncertainty for ten input parameters. Sixteen output parameters were selected for uncertainty evaluation and uncertainty band between $5^{th}$ and $95^{th}$ percentile of the output parameters were evaluated. It was observed that the uncertainty band for the primary pressure during two phase blowdown is larger than that of the remaining period. Similarly, a larger uncertainty band is observed relating to accumulator injection flow during reflood phase. Importance analysis was also carried out and standard rank regression coefficients were computed to quantify the effect of each individual input parameter on output parameters. It was observed that the break discharge coefficient is the most important uncertain parameter relating to the prediction of all the primary side parameters and that the steam generator (SG) relief pressure setting is the most important parameter in predicting the SG secondary pressure.