• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.97-106
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• 2009

WLAN(wireless local area network)-based positioning is the most attractive because it does not require any special equipments dedicated for positioning even though it is less accurate than the other strategies. Applying our WLAN-based decision tree method for indoor positioning, we obtained pedestrian's tracks, and performed stochastic confidence tests on the tracks in order to validate them.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.72-73
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• 2018

The accuracy of contingency estimation plays an important role for dealing with the uncertainty of the financial success of construction project. Its' estimation may be used for various purposes such as schedule control, emergency resolve, and quality expense, etc. This paper presents a contingency estimation method which is schedule control specific. The method 1) implements stochastic EVMS, 2) detects a specific timing for schedule compression, 3) identifies an optimal strategy for shortening planned schedule, 4) finds a probability density function (PDF) of project cost overrun, and 5) estimates the optimal contingency cost based on the level of confidence. The method facilitates expeditious decisions involved in project budgeting. The validity of the method is confirmed by performing test case.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.46-49
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• 1998

In this paper, we introduce the notion of intelligent communication by introducing a novel intelligent receiver model. This receiver is continually evolving and learns and improves in performance as it compiles its experience over time. In digital communication context, in a typical training mode, it jearns the concept of "1" as is deteriorated by arbitrary (not necessarily additive as is typically assumed) disturbance and /or modulation. After learning "1", in test mode, it classifies the received signal "1" and "0" almost completely. The intelligent receiver as implemented is grounded on the recently introduced Stochastic Morphological Sampling Theorem(SMST), a distribution-free result which gives theoretical bounds on the sample complexity(training size) needed for the required performance parameters such as accuracy($\varepsilon$) and confidence($\delta$). Based on this theorem, we demonstrate --almost irrespective of channel and modulation model-- the number of samples needed to learn the concept of "1" is not too "large" and the resulting universal receiver structure, that corresponding to classical Nearest Neighbor rule in Pattern Recognition Theory, is trivial. We check the surprising efficiency and validity of this model through some simple simulations. and validity of this model through some simple simulations.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.655-661
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• 2020

In this study, the correlation between concrete core compressive strength and rebound hardness of urban railway underground structures was analyzed. The equations for the range of rebound hardness were derived and compared with the measured concrete core strengths for each range of rebound hardness to confirm the adequacy of the estimated compressive strength. As the result, the linear regression analysis results of the average compressive strength by the Gaussian probability density function (representative compressive strength estimation formula) and the estimation formula by the rebound hardness range were founded to match well within 3% of the experimental concrete core compressive strength test results. Therefore, the stochastic statistical analysis using the rebound hardness measurement results suggested in this study could be help to secure the confidence level of the correlation between the rebound hardness and the concrete compressive strength which are relatively large deviation according to the estimation equations.