• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.327-327
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• 2019

The study will quantify the total uncertainties in streamflow and precipitation projections for Upper Awash River Basin located in central Ethiopia. Three hydrological models (GR4J, CAT, and HBV) will be used to simulate the streamflow considering two emission scenarios, six high-resolution GCMs, and two downscaling methods. The readily available hydrometeorological data will be applied as an input to the three hydrological models and the potential evapotranspiration will be estimated using the Penman-Monteith Method. The SCE-UA algorithm implemented in PEST will be used to calibrate the three hydrological models. The total uncertainty including the incremental uncertainty at each stage (emission scenarios and model) will be presented after assessing a total of 24 (=$2{\times}6{\times}2$) high-resolution precipitation projections and 72 (=$2{\times}6{\times}2{\times}3$) streamflow projections for the study basin. Finally, the primary causes that generate uncertainties in future climate change impact assessments will be identified and a conclusion will be made based on the finding of the study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.137-146
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• 2016

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer's capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer's skill-level. This study intends to social contribution through attempts to optimize enterprise's goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource's capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz's MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.373-384
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• 2020

Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.483-503
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• 2017

Uncertainty is a fact belonging to engineering practice. An important uncertainty that sets geotechnical engineering is the variability associated with the properties of soils or, more precisely, the characterization of soil profiles. The reason is due largely to the complex and varied natural processes associated with the formation of soil. Spatial variability analysis for the study of the stability of natural slopes, complementing conventional analyses, is able to incorporate these uncertainties. In this paper the characterization is performed in back-analysis for a case of landslide occurred to verify afterwards the presence of the conditions of shear strength at failure. This approach may support designers to make more accurate estimates regarding slope failure responding, more consciously, to the legislation dispositions about slope stability evaluation and future design. By applying different kriging techniques used for spatial analysis it has been possible to perform a 3D-slope reconstruction. The predictive analysis and the areal mapping of the soil mechanical characteristics would support the definition of priority interventions in the zones characterized by more critical values as well as slope potential instability. This tool of analysis aims to support decision-making by directing project planning through the efficient allocation of available resources.

• Knowledge Management Research
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• v.20 no.1
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• pp.175-194
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• 2019

In order to overcome the limitation of market orientation concept, Narver et al. (2004) have extended the original concept into two dimensions, responsive market orientation (RMO) and proactive market orientation (PMO), respectively. Yet, there has been very limited empirical studies that analyzed the differential effects of each market orientation on firm outcomes, especially in the Korean context. We analyze the impact of RMO and PMO on the new product performance in the perspective of SMEs and examine the moderating effect of external factors such as environmental uncertainty and market similarity. The results of this study show that both RMO and PMO have a significant positive effect on the new product performance of SMEs. Also, environment uncertainty shows a negative moderating effect on the relationship between RMO and new product performance, whereas it has positive moderation with PMO. This suggests that focusing on potential customers' needs rather than current needs helps improve firm performance as the competitive environment surrounding the firm becomes more uncertain. Lastly, market similarity showed a positive moderating effect on the relationship between RMO and new product performance, but not on PMO.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• The Journal of the Korea Contents Association
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• v.15 no.9
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• pp.84-95
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• 2015

The aim of this research is to find out how to cope with and manage environmental uncertainty to be effective. Environmental conditions of complexity and change create a greater need to gather information and to respond based on that information. Despite of the governmental campaign 'creative economy, flourishing culture', governmental subsidies are becoming more unstable. The prosperity of culture means that artists can create great works and people can enjoy them without boundaries. This research investigated Boundary-spanning roles through the strategic formulation and implementation. Key factors of strategy are information and knowledge management. Boundary-spanning roles link and coordinate an organization with important elements in the external environment. It is primarily concerned with the exchange of information to detect and bring into the organization information about changes in the environment and send information into the environment that presents the organization in a favorable light. Two themes in this article are that organizations can learn and adapt to the environment and that organizations can change and control the environment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.307-316
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• 2019

In the agricultural sector, greenhouse gas emissions vary depending on the interaction of all ecosystem changes such as soil environment, weather environment, crop growth, and anthropogenic farming activities. Agricultural sector greenhouse gas emissions resulting from many of these interactions are highly variable. Uncertainty-based evaluation that defines the interval with confidence level of greenhouse gas emission and absorption is necessary to take account of the variance characteristics of individual emissions, but research on uncertainty evaluation method is insufficient. This study aims to decide on the effect of reducing N₂O emissions from upland soils using an uncertainty-based approach. An uncertainty-based approach confirmed whether there was a difference between confidence intervals in the 5 different fertilizer treatment groups to reduce greenhouse gas emissions. Unlike the statistically significant test with three repetition averages, the uncertainty-based approach method estimated in this study is able to estimate the confidence interval considering the distribution characteristics of the emissions, such as the dispersion characteristics of individual emissions. Therefore, it is considered that the reliability of emissions can be improved by statistically testing the variance characteristics of emissions such as the uncertainty-based approach. It is hoped that the direction of the uncertainty-based approach for the effect of reducing greenhouse gas emissions in agriculture will be helpful in the future development of agricultural greenhouse gas emission reduction technology, adaptation to climate change, and further development of sustainable eco-social system.

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.35-42
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• 2022

This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.

• The Journal of the Korea Contents Association
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• v.13 no.7
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• pp.168-180
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• 2013

Based on the strategic contingency theory, this study empirically examines Korean TV drama producers' changing adaptive behaviors in terms of genre variety given different levels of environmental uncertainty. The extant literature has suggested that firms tend to increase product variety in order to cope with increasing environmental uncertainty. This study attempted to verify the hypothesis that TV drama producers would employ wider variety of genre in the period with more uncertain environment(2003-2009) than the period with stable environment(1994-2002). Empirical results support the hypothesis, implying that TV drama producers tend to repeatedly produce dramas with the same genre in order to pursue efficiency in stable environment whereas they tend to employ a variety of different genre in order to cope with increasing environmental uncertainty.