• 스트레스연구
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• 제26권4호
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• pp.350-355
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• 2018

본 연구에서는 불확실성에 대한 인내력 부족과 부정적인 문제해결 지향 및 걱정간의 관계를 알아보고자 하였다. 이를 위해 충북에 소재한 4년제 대학교에 재학 중인 531명을 대상으로 불확실성에 대한 인내력 부족, 부정적인 문제해결 지향, 걱정에 관한 설문지를 실시하여 자료를 수집하였다. 그 결과, 불확실성에 대한 인내력 부족과 부정적인 문제해결 지향과의 상관이 유의하였다. 또한 불확실성에 대한 인내력 부족과 걱정 간의 관계에서 부정적인 문제해결 지향이 매개효과를 지니는 것으로 나타났다. 이로 볼 때, 걱정이 높은 사람들을 대상으로 불확실성에 대한 인내력과 부정적인 문제해결 지향에 초점을 두어 개입을 하는 것이 유용할 수 있겠다. 추가적으로 본 연구의 의의와 한계점에 대해서도 논의하였다.

• Structural Engineering and Mechanics
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• 제32권1호
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• 대한기계학회논문집A
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• 제33권10호
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• pp.1163-1170
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• 2009

Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.321-344
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• 2017

Smart homes are the new generation of homes where pervasive computing is employed to make the lives of the residents more convenient. Human activity recognition (HAR) is a fundamental task in these environments. Since critical decisions will be made based on HAR results, accurate recognition of human activities with low uncertainty is of crucial importance. In this paper, a novel HAR method based on a difference of convex programming (DCP) problem is represented, which manages to handle uncertainty. For this purpose, given an input sensor data stream, a primary belief in each activity is calculated for the sensor events. Since the primary beliefs are calculated based on some abstractions, they naturally bear an amount of uncertainty. To mitigate the effect of the uncertainty, a DCP problem is defined and solved to yield secondary beliefs. In this procedure, the uncertainty stemming from a sensor event is alleviated by its neighboring sensor events in the input stream. The final activity inference is based on the secondary beliefs. The proposed method is evaluated using a well-known and publicly available dataset. It is compared to four HAR schemes, which are based on temporal probabilistic graphical models, and a convex optimization-based HAR procedure, as benchmarks. The proposed method outperforms the benchmarks, having an acceptable accuracy of 82.61%, and an average F-measure of 82.3%.

• 한국물환경학회지
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• 제29권5호
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.

• Earthquakes and Structures
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• 제26권4호
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• pp.311-326
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• 2024

Transmission tower structures are particularly susceptible to damage and even collapse under strong seismic ground motions. Conventional seismic analyses of transmission towers are usually performed by considering only ground motion uncertainty while ignoring structural uncertainty; consequently, the performance evaluation and failure prediction may be inaccurate. In this context, the present study numerically investigates the seismic responses and failure mechanism of transmission towers by considering multiple sources of uncertainty. To this end, an existing transmission tower is chosen, and the corresponding three-dimensional finite element model is created in ABAQUS software. Sensitivity analysis is carried out to identify the relative importance of the uncertain parameters in the seismic responses of transmission towers. The numerical results indicate that the impacts of the structural damping ratio, elastic modulus and yield strength on the seismic responses of the transmission tower are relatively large. Subsequently, a set of 20 uncertainty models are established based on random samples of various parameter combinations generated by the Latin hypercube sampling (LHS) method. An uncertainty analysis is performed for these uncertainty models to clarify the impacts of uncertain structural factors on the seismic responses and failure mechanism (ultimate bearing capacity and failure path). The numerical results show that structural uncertainty has a significant influence on the seismic responses and failure mechanism of transmission towers; different possible failure paths exist for the uncertainty models, whereas only one exists for the deterministic model, and the ultimate bearing capacity of transmission towers is more sensitive to the variation in material parameters than that in geometrical parameters. This research is expected to provide an in-depth understanding of the influence of structural uncertainty on the seismic demand assessment of transmission towers.

• Asia Marketing Journal
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• 제19권1호
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• pp.19-34
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• 2017

Despite the importance of the impact of network structure on the relationships between firms and firm performance, few studies have investigated these effects. This study investigates how network openness influences the relationships between TSI, opportunism, technological uncertainty, and supplier performance. We also try to figure out how network openness functions as a governance mechanism.

• 유통과학연구
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• 제15권9호
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• pp.95-107
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• 2017

Purpose - In the joint development of new products, buyers and suppliers exchange information to solve various problems. Uncertainty and ambiguity are typical examples. Uncertainty refers to the lack of information to solve the problem, and equivocality refers to the case where the information is interpreted in multiple processes in the process of providing the information. These uncertainty and equivocality cause new products to be delayed in their development and adversely affect quality. However, unfortunately, there is a lack of researches on how the uncertainty and equivocality of such concepts control the results of new product joint development. But, smooth communication and effective exchange of information is not emphasized only in the general organization. The importance of the new product joint development projects to achieve the two organizations' common goals becomes even greater. The purposes of this study are to analyse the effect of supplier's strategy on the NPD performance and moderating effect of uncertainty and equivocality. Research design, data, and methodology - In order to make a contribution to the lack of academic researches in Korea, this study collects data through questionnaires based on organizational information processing theory and previous studies, and conducts empirical analysis. Results - As a result, the product modularization strategy and the strategic supply chain relationship positively influenced the new product development performance - return on investment and ease of manufacturing. And the interaction effect of uncertainty and equivocality with supplier's strategy - product modularity strategy and strategic supply chain management relationship - reduces or negates the influence of product modularization strategy on new product development performance. Conclusions - This implies that it is important to control uncertainty and equivocality in order for the supplier strategy to have a positive effect on new product development performance. It also emphasizes the necessity of sharing information appropriately for companies that do not want to share the information as possible due to their fear of loss of competitive advantage in the joint development of new products. Because this kind of negative policy might let uncertainty and equivocality be happen in new product joint development process.

• 한국문헌정보학회지
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• 제53권3호
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• pp.247-271
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• 2019

과학에서 지식의 불확실성은 명제가 현재 상태로는 참도 거짓도 아닌 불확실한 상태를 의미한다. 기존의 연구들은 학술 문헌에 표현된 명제를 분석하여 불확실성을 의미하는 단어를 수동적으로 구축하고 구축한 코퍼스를 대상으로 규칙 기반, 기계 학습 기반의 성능평가를 수행해왔다. 불확실성 단어 구축의 중요성은 인지하고 있지만 단어의 의미를 분석하여 자동적으로 확장하고자 하는 시도들은 부족했다. 한편, 계량정보학이나 텍스트 마이닝 기법을 이용하여 네트워크의 구조를 파악하는 연구들은 다양한 학문분야에서 지적 구조와 관계성을 파악하기 위한 방법으로 널리 활용되고 있다. 따라서, 본 연구에서는 기존의 불확실성 단어를 대상으로 Word2Vec을 적용하여 의미적 관계성을 분석하였고, 영어 어휘 데이터베이스이자 시소러스인 WordNet을 적용하여 불확실성 단어와 연결된 상위어, 하위어 관계와 동의어 기반 네트워크 분석을 수행하였다. 이를 통해 불확실성 단어의 의미적, 어휘적 관계성을 구조적으로 파악하였으며, 향후 불확실성 단어의 자동 구축의 확장 가능성을 제시하였다.

• 산업공학
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• 제6권2호
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• pp.67-78
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• 1993

In this paper, we deal with the application of the fuzzy sets theory to evaluate and estimate the system reliability under the fault tree analysis. We formulate the uncertainty of component reliability to fuzzy sets, and propose a procedure for obtaining the system reliability in case the system structure is described by fault tree. An importance measure of each component is proposed. Computer program for fuzzy fault tree analysis(FFTA) is developed using C language to obtain the system reliability and the component‘s fuzzy importance.