• The KIPS Transactions:PartB
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• v.13B no.7 s.110
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• pp.633-642
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• 2006

In the Internet environment many interactions between many users and unknown users take place and it is usually rare to have the trust information about others. Due to the lack of trust information, entities have to take some risks in transactions with others. In this perspective, it is crucial for the entities to be equipped with functionality to accumulate and manage the trust information on other entities in order to reduce risks and uncertainty in their transactions. This paper is concerned with a quantitative computational trust model which takes into account multiple evaluation criteria and uses the recommendation from others in order to get the trust for an entity. In the proposed trust model, the trust for an entity is defined as the expectation for the entity to yield satisfactory outcomes in the given situation. Once an interaction has been made with an entity, it is assumed that outcomes are observed with respect to evaluation criteria. When the trust information is needed, the satisfaction degree, which is the probability to generate satisfactory outcomes for each evaluation criterion, is computed based on the empirical outcome outcome distributions and the entity's preference degrees on the outcomes. Then, the satisfaction degrees for evaluation criteria are aggregated into a trust value. At that time, the reputation information is also incorporated into the trust value. This paper also shows that the model could help the entities effectively choose other entities for transactions with some experiments in e-commerce.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.153-164
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• 1998

본 논문은 2-상태 시스템의 신뢰도 계산을 위하여 Heidtmann[3]이 제시한 가역 알고리즘을 부울 대수를 사용하여 경로집합으로부터 절단집합을 유도하거나, 역으로 절단집합으로부터 경로집합을 유도함으로서 효율성을 입증하였으며, 포함-불포함 공식(inclusion-exclusion formula)과 추축 분해법칙(pivotal decomposition rule)을 이용하여 직·병렬구조 및 복합구조의 신뢰도를 계산할 수 있는 알고리즘을 개발, 분석하였다.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.629-640
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• 2010

The exemplar-based inpainting model is widely used to remove objects from natural images and to restore a damaged region. This paper presents a method which improves the performance of the conventional exemplar-based inpainting model by modifying three major parts in the model: data term, confidence term and patch selection. While the conventional data term is calculated using the local gradient, the proposed method uses 16 compass masks to get the global gradient to make the method robust to noise. To overcome the problem that the confidence term gets negligible in the inside of the eliminated region, a method is proposed which makes the confidence term decrease slowly in the eliminated region. The patch selection procedure is modified so that the closer patch has higher weight. Experiments showed that the proposed method produced more natural images and lower reconstruction error than the conventional exemplar-based inpainting.

• Composites Research
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• v.23 no.2
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• pp.40-47
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• 2010

In this paper, the hybrid response surface method(HRSM) is proposed and examined. Hybrid response surface method calculate a approximate model repeatedly based on MPP coordinates. To verify the performance, probability of failure, MPP(Most Probable failure Point) and reliability index are calculated for nonlinear function and composite laminated plate by using reliability analysis method and compared with results by using typical response surface method(RSM). Probability of failure is calculated under the assumption of the nonlinear limit state equation and given failure criterion. The results of proposed method shows performance improvement in estimating the probability of failure.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.293-301
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• 2001

This paper reviews three methods to compute a pointwise confidence interval of neuro-fuzzy models and compares their estimation perfonnanee through simulations. The eOITl.putation methods under consideration include stacked generalization using cross-validation, predictive error bar in regressive models, and local reliability measure for the networks employing a local representation scheme. These methods implemented on the neuro-fuzzy models are applied to the problems of simple function approximation and chaotic time series prediction. The results of reliability estimation are compared both quantitatively and qualitatively.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.92-100
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• 2016

Reliability analysis of tripod support structure for offshore wind turbine was performed. Extreme distribution function of peak response due to wind and wave loads was estimated by applying peak over threshold(POT) method. Then, stress based limit state function was defined by using maximum stress of support structure which was obtained by multiplying beam stress and concentration factor. The reliability analysis result was compared when maximum stress was calculated from shell element. Reliability index was evaluated using first order reliability method(FORM).

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.05a
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• pp.350-353
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• 2009

In the fatigue analysis and the components design, uncertainties are caused by the variances of geometry data and applied loads, and the scatter of material properties. In this paper, fatigue crack growth life of turbine is evaluated by fracture mechanics and the reliability analysis is accessed by the fist order second moment method and Monte Carlo simulation.

• International Commerce and Information Review
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• v.17 no.3
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• pp.155-176
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• 2015

This study examines the close relationship between trust and global business negotiations. Kristen Blankley(2010) pointed out three level of trust impacting each negotiation stage: calculus-, knowledge-, identification-based trust. In this regard, the present study examines the relationship between each level of trust and the process of business negotiations by focusing on Canadians and Koreans who had business negotiation experience with Chinese counterparts. For Canadian respondents, calculus-based trust and identification-based trust didn't have significant effects on the negotiation atmosphere, whereas they did for Korean respondents. For Canadian respondents, knowledge-based trust had the greatest effect on each step of the business negotiation process.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.567-575
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• 2017

Location-based services play an important role in many applications such as disaster warning systems and recommendation systems. These applications often require not only location information (e.g., name, latitude, longitude, etc.) but also the impact of events (e.g., earthquake, typhoon, etc.) on locations. Recently, to provide the impact of an event on a location, how to calculate location trustiness by using multimodal information such as earthquake information and disaster sensor data is researched. In the previous approach, the linear decrement of impact value of an event is applied to obtain the location trustiness of a specific location. In this paper, we propose a new approach to enrich location trustiness, that is, the impact of an event on a location, by using social media information additionally. Firstly, we design a collecting system for earthquake information and social media data. Secondly, we present an approach of location trustiness calculation based on earthquake information. Finally, we propose a new approach to enrich location trustiness by augmenting the trustiness in spatially distributed manner based on social media.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.505-514
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• 2000

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.