• 기술혁신학회지
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• 제12권1호
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• pp.212-236
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• 2009

본 연구는 차세대 컨버전스서비스를 대상으로 고객, 기술, 사업자, 규제의 4대 이슈별로 환경 불확실성요인을 규명하고, 이들 환경 불확실성요인 중 특히 핵심이 되는 불확실성 요인을 도출하였다. 이어 도출된 핵심불확실성요인(KUF: Key Uncertainty Factor)을 중심으로 환경의 잔여불확실성 수준에 대한 평가를 시나리오 플래닝에 의해 실시하고, 이를 기반으로 차세대 컨버전스서비스의 진입전략 수립을 위한 방향을 제시하였다. 본 연구의 차세대 컨버전스서비스 사업의 불확실성 평가 및 진입 시나리오 구성에 대한 연구결과를 종합하면 다음과 같다. 2가지 잔여 불확실성 수준(선택 가능한 미래 수준, 예측 범위의 미래 수준)의 6개 시나리오를 대상으로 각각의 전략적 속성을 평가한 결과 시장 진입의 성공 요소로 2가지 핵심성공요인(KSF: Key Success Factor)을 도출하였다. 즉, 고객수요추세, 광고규제 완화를 핵심성공요인(KSF: Key Success Factor)으로 도출하였으며, 이를 토대로 4가지 전략적 시나리오 유형 및 각 시나리오 별 요구되는 사업자 대응역량에 대한 방향성을 제시하였다. 본 연구의 결과는 컨버전스 시장의 활성화는 물론 관련 사업자의 자원의 효율적 배분, 진입형태, 진입 적정시기 등 진입전략 수립에 많은 시사점을 제공할 것이다.

• 기술혁신연구
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• 제20권3호
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• pp.1-28
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• 2012

본 연구에서는 시나리오 기반의 전략적 미래예측을 통하여 2030년경 우리나라의 원전산업 분야를 정성적으로 분석하였다. 구체적으로 STEEP맵 작성과 네트워크 분석(Network Analysis)을 활용하여 다차원적인 관점에서 미래원전산업 분야 환경변화 영향요인간의 관계성을 규명하였다. 이어 시나리오 기법을 활용하여 미래원전산업의 핵심 불확실성 요인(Key Uncertainty Factor: KUF)을 중심으로 예상 가능한 3가지의 전략적 시나리오 (Optimistic, Business as usual, Pessimistic)를 생성하고, 해외 원전수출을 위해 정부가 시급히 추진해야 될 시나리오별 공통전략과 최대 위험회피 전략도 함께 제시하였다. 본 연구결과를 통해 에너지 가격, 세계 경기 동향, 원전기술 경쟁력, 원전 마케팅 능력 등이 미래 원전산업 분야의 핵심 불확실성 요인으로 작용함을 알 수 있었다. 또한, 실효성 있는 미래원전 산업의 수출전략 마련을 위해서는 '원전 안전 등 기술력 확보', '원전 인력 확보', '우라늄 등 안정적 자원 확보' 및 '원전 수용성 증대'등에 관한 전략 추진이 중요 정책과제로 상정되어야 함을 제안 하였다. 끝으로 이러한 연구결과에 따른 시사점과 연구의 한계에 대하여 논의하였다.

• Smart Structures and Systems
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• 제29권2호
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• 한국건축시공학회지
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• 제8권4호
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• pp.53-59
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• 2008

Cost estimates are very important to their decision-making in the early stages of a construction project. So Clients have wanted not only to know the results of conceptual cost estimates but also to assess their quality Conceptual cost estimates process is very complex process, so the results of cost estimates are influenced by various factors. So the purpose of this study is to reveal the key factors which influence the reliability of conceptual cost estimates in building construction projects. The analytic hierarchy process is used to determine the relative important weights of elements influencing the conceptual cost estimates. And factor analysis is used to reveal the key factors from the elements that influence the conceptual cost estimates. The results showed that the key factors is an experience level, available data level, level of will for winning the bid, difficulty level of conceptual cost estimate, uncertainty level.

• 무역학회지
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• 제47권1호
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• pp.25-42
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• 2022

This study identified consumers' shopping behavior in live streaming commerce. To this end, this study put the uncertainty issue of live shopping and the transfer of trust at the center of the discussion. The verification of the research model resulted in the following conclusions. First, reduced uncertainty in live shopping was a factor in increasing the level of involvement and attachment in the service. These results showed that resolving uncertainty in newly introduced services is a key factor in determining users' positive attitudes. Second, the trust in shopping sites influenced the current live shopping attitude. This is because the transfer of trust is also valid in live shopping, which demonstrated the importance of building trust. Third, this study proposed and validated a research model that could systematically understand the consumption process of live streaming shopping. Furthermore, this study provides a beneficial implication for those who want to use live shopping in practice.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.859-861
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• 1996

This paper presents the novel fault diagnostic expert system based on dissolved gas analysis(DGA) techniques in power transformer. The uncertainty of key gas analysis, norm threshold, and gas ratio boundaries are managed by using a fuzzy set concept. The uncertainty of rules are handled by fuzzy measures. Trend analysis through the monthly increment of key gas and DGA analysis are combined by the Dempster-Shafer theory, and the state of transformer and confidence factor are yielded by using this combined analysis. To verify the effectiveness of the proposed diagnosis technique, the expert system has been tested by using KEPCO's transformer gas records.

• Wind and Structures
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• 제22권1호
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• pp.17-41
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• 2016

To address the uncertainty of the flight trajectories caused by the turbulence and gustiness of the wind field over the roof and in the wake of a building, a 3-D probabilistic trajectory model of flat-type wind-borne debris is developed in this study. The core of this methodology is a 6 degree-of-freedom deterministic model, derived from the governing equations of motion of the debris, and a Monte Carlo simulation engine used to account for the uncertainty resulting from vertical and lateral gust wind velocity components. The influence of several parameters, including initial wind speed, time step, gust sampling frequency, number of Monte Carlo simulations, and the extreme gust factor, on the accuracy of the proposed model is examined. For the purpose of validation and calibration, the simulated results from the 3-D probabilistic trajectory model are compared against the available wind tunnel test data. Results show that the maximum relative error between the simulated and wind tunnel test results of the average longitudinal position is about 20%, implying that the probabilistic model provides a reliable and effective means to predict the 3-D flight of the plate-type wind-borne debris.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권4호
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• pp.499-507
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• 2018

Autonomous Underwater Vehicle (AUV), which are becoming more and more important in ocean exploitation tasks, needs energy conservation urgently when sailing the complex mission path in long time cruise. As hull lines optimization design becomes the key factor, which closely related with resistance, in AUV preliminary design stage, uncertainty parameters need to be considered seriously. In this research, Myring axial symmetry revolution body with parameterized expression is assumed as AUV hull lines, and its travelling resistance is obtained via modified DATCOM formula. The problems of AUV hull lines design for the minimum travelling resistance with uncertain parameters are studied. Based on reliability-based optimization design technology, Design For Six Sigma (DFSS) for high quality level is conducted, and is proved more reliability for the actual environment disturbance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• Structural Engineering and Mechanics
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• 제57권2호
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• pp.369-387
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• 2016

In this work, random homogenization analysis for the effective thermal properties of a three-dimensional composite material with unidirectional fibers is presented by combining the equivalent inclusion method with Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are completely accounted for, and stochastic effective thermal properties as thermal expansion coefficients as well as their correlation are then sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared. The impact of randomness and correlation of the micro-structural parameters on the random homogenized results is revealed by two methods simultaneously, and some important conclusions are obtained.