• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.57-64
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• 2005

LBL(Layer-By-Layer) algorithms have been proposed to accelerate the training speed of MLPs(Multilayer Perceptrons). In this LBL algorithms, each layer needs a error function for optimization. Especially, error function for hidden layer has a great effect to achieve good performance. In this sense, this paper proposes a new hidden layer error function for improving the performance of LBL algorithm for MLPs. The hidden layer error function is derived from the mean squared error of output layer. Effectiveness of the proposed error function was demonstrated for a handwritten digit recognition and an isolated-word recognition tasks and very fast learning convergence was obtained.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.1
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• pp.51-58
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• 2021

As vertical extension remodeling policy was implemented in 2014, Safety Inspection Manual was established to ensure structural safety during the vertical extension remodeling. In the manual, the story weight for capability evaluation was based on the Safety Inspection Manual for Reconstruction. Although capability evaluation in the vertical extension remodeling is more important than reconstruction, engineering basis for the story weight is insufficient. Therefore it is necessary to improve the method of calculating the story weight. In this study, story importance and story weight were defined through the case analysis of capability evaluation in order to provide engineering basis for story weight. Also, new story weight equation was presented considering the load-bearing ratio of structural members.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1047-1061
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• 2015

Stratified random sampling is a powerful sampling strategy to reduce variance of the estimators by incorporating useful auxiliary information to stratify the population. Sample allocation is the one of the important decisions in selecting a stratified random sample. There are two common methods, the proportional allocation and Neyman allocation if we could assume data collection cost for different observation units equal. Theoretically, Neyman allocation considering the size and standard deviation of each stratum, is known to be more effective than proportional allocation which incorporates only stratum size information. However, if the information on the standard deviation is inaccurate, the performance of Neyman allocation is in doubt. It has been pointed out that Neyman allocation is not suitable for multi-purpose sample survey that requires the estimation of several characteristics. In addition to sampling error, non-response error is another factor to evaluate sampling strategy that affects the statistical precision of the estimator. We propose new sample allocation methods using the available information about stratum response rates at the designing stage to improve stratified random sampling. The proposed methods are efficient when response rates differ considerably among strata. In particular, the method using population sizes and response rates improves the Neyman allocation in multi-purpose sample survey.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.364-370
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• 2005

LBL(Layer-By-Layer) algorithms have been proposed to accelerate the training speed of MLPs(Multilayer Perceptrons). In this LBL algorithms, each layer needs a error function for optimization. Especially, error function for hidden layer has a great effect to achieve good performance. In this sense, this paper proposes a new hidden layer error function for improving the performance of LBL algorithm for MLPs. The hidden layer error function is derived from the mean squared error of output layer. Effectiveness of the proposed error function was demonstrated for a handwritten digit recognition and an isolated-word recognition tasks and very fast learning convergence was obtained.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.717-721
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• 2012

유속(혹은 난류강도) 증감에 따른 floc 특성의 변화를 파악하기 위하여, 현재 연안 개발이 활발히 수행되고 있는 목포해역을 대상으로 ADCP를 이용한 층별 유속 및 부유사 농도의 연속관측이 수행되었다. 목포해역 내 대표정점에서 층별로 유속 유향 및 음파 intensity와 함께 전체 수심데이터가 5분 간격으로 측정되었으며, ADCP 음파의 intensity와 부유사 농도의 상관관계 분석을 위하여 동일 시간동안 채수기를 이용하여 water sampling(30분 간격) 또한 동시에 수행되었다. 관측시간 동안의 목포해역은 낙조류의 흐름특성을 가지며, 표층에서의 최강유속은 24.5cm/s, 유향은 대체적으로 NW~N향 사이에 분포하는 것으로 나타났다. 또한 층별 부유사 농도는 그 차이가 매우 미미한 것으로 나타났다. 본 연구를 통하여 관측된 자료들은 퇴적물의 제반 이송특성 연구를 위한 기초자료로 활용될 수 있을 뿐만 아니라, 향후 퇴적물 이송 및 수질 예측/평가를 위한 수치모형 적용시 입력자료로 유용하게 사용될 수 있을 것이다.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.671-683
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• 2021

Power allocation is a technique that evenly allocates samples for each stratum, although the overall efficiency of the allocation is less than that of optimal allocation, and it is often used as a square root proportional allocation in real survey. Also, considering the non-response that occurs in real survey, a larger sample size is used than that in the theoretical formula. In this study, in determining the sample size for each stratum, we study the new methods of allocating by adding information on the response rate per each stratum to power allocation method. The proposed allocation methods are compare with proportional, optimal, and square root proportional allocation in simulation. In addition, the comparison with the proportional and optimal allocation to which the response rate was added is examined through simulation. As a result, we examine the advantages and disadvantages of the allocation methods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.452-453
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• 2008

pin 두 개의 층으로 이루어진 적층형 박막 태양전지를 이용하여 시뮬레이션 하였다. 각 층별 두께를 조절하여 층별 효율을 측정 하였다. 또한 각 층의 도핑 농도를 조절하여 층별 효율을 측정하였다. 그 후 각각 두 개의 층의 최대효율을 측정하였고 동일한 값으로 두 층이 직렬 연결된 태양전지의 효율을 측정하였다. 그 결과 최대 10.14%로 측정 되었다.

• 월간 기계설비
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• s.67
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• pp.96-103
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• 1996

• 월간 기계설비
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• s.90
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• pp.91-104
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• 1998

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.2
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• pp.189-196
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• 2009

This paper presents the subparametric finite element model formulated by partial-linear layerwise theory for the analysis of laminate composites. The proposed model is based on refined approximations of two dimensional plane for orthotropic thick laminate plate as well as thin case. Three dimensional problem can be reduced to two dimensional case by assuming piecewise linear variation of in-plane displacement and a constant value of out-of-plane displacement across the thickness. The integrals of Legendre polynomials are chosen to define displacement fields and Gauss-Lobatto numerical integration is implemented in order to directly obtain maximum values occurred at the nodal points of each layer without other extrapolation techniques. The validity and characteristics of the proposed model have been tested by using orthotropic multilayered plate problem as compared to the values available in the published references. In this study, the convergence test has been carried out to determine the optimal layer model in terms of central deflection and stresses. Also, the distribution of displacements and stresses across the thickness has been investigated as the number of layer is increased.