• Proceedings of the KSEEG Conference
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• 2003.04a
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• pp.135-138
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• 2003

대부분의 제4기단층은 제3기 단층이 재활동한 것들로써, 신기 조구조적 단층 여부를 규명하려면, 제4기에 형성된 단구(段丘, Terrace)의 변위가 수반 증명되어야한다. 대표적인 단층은 읍천단층과 수렴단층을 들 수 있다. 특히 읍천단층은 기반암단층으로 언급될 경우에는 읍천 단층이라 하고, 제4기에 재활동한 부분을 거론할 경우에는 제4기 읍천단층이라고 구분하여 혼란을 피하도록 하였다. (중략)

• Journal of the Korean association of regional geographers
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• v.18 no.4
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• pp.351-363
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• 2012

Although the Korean peninsula has been considered as a largely aseismic region compared with the surrounding high seismic areas such as North China and Japan, there are more than thirty Quaternary faults reported so far, which are mostly centered in the southeastern peninsula. Structural studies of active faults exposed in Yangnam-myeon of Gyeongju, SE Korea are largely interpreted to post date the late Quaternary, suggesting that the NE-trending reverse faults may result from the active stress regime in the peninsula. The prevailing present-day E-W $S_{Hmax}$ orientations in the peninsula are consistent with the nature of plate forcing stemming from the convergence between the Indo-Australian and Eurasian plates. It is clear that the Quaternary faults have been reactivated, although resolving more elaborate time intervals responsible for a future rupture remains a significant challenge. This study contributes to better assess many of potential seismic hazards in the study area, in particular, in terms of seismic stability for foundation of nuclear power plant.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.447-452
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• 2005

기존의 단층 퍼셉트론은 출력 노드가 선형 분리 가능한 패턴들만을 분류할 수 있고 Exclusive OR와 같은 비선형 문제에 대해서는 분류할 수 없는 단점이 있다. 그러나 퍼지 단층 퍼셉트론은 퍼지소속 함수(fuzzy membership function)를 적용하여 단층 구조로 Exclusive OR 문제와 같은 고전적인 문제를 개선하였다. 그러나 퍼지 단층 퍼셉트론은 기존의 단층 퍼셉트론과 마찬가지로 결정 경계선이 진동하는 경우가 생기며 초기 가중치의 범위와 학습률에 따라 수렴성이 매우 낮아지는 단점이 있다. 따라서 본 논문에서는 바이어스항을 도입하여 결정 경계선이 진동하는 것을 방지하여 수렴성을 개선시키고 선형 활성화 함수를 제안하고 학습률과 모멘텀 개념을 도입하여 학습 시간을 단축시키는 개선된 퍼지 단층 퍼셉트론 알고리즘을 제안한다. 제안된 방법과 퍼지 단층 퍼셉트론간의 학습 성능을 분석하기 위하여 인공 신경망에서 벤치마크로 사용되는 exclusive OR 문제와 문자 패턴 분류에 적용하여 epoch 수와 수렴성을 비교한 결과, 제안된 방법이 기존의 퍼지 단층 퍼셉트론보다 학습 시간이 적게 소요되고 수렴성이 개선된 것을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1387-1393
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• 2007

Even if the linearly separable patterns can be classified by the conventional single layer perceptron, the non-linear problems such as XOR can not be classified by it. A fuzzy single layer perceptron can solve the conventional XOR problems by applying fuzzy membership functions. However, in the fuzzy single layer perception, there are a couple disadvantages which are a decision boundary is sometimes vibrating and a convergence may be extremely lowered according to the scopes of the initial values and learning rates. In this paper, for these reasons, we proposed an enhanced fuzzy single layer perceptron algorithm that can prevent from vibration the decision boundary by introducing a bias term and can also reduce the learn time by applying the modified delta rule which include the learning rates and the momentum concept and applying the new linear activation function. Consequently, the simulation results of the XOR and pattern classification problems presented that the proposed method provided the shorter learning time and better convergence than the conventional fuzzy single layer perceptron.

• The Journal of the Petrological Society of Korea
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• v.23 no.3
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• pp.187-195
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• 2014

In this paper, we report new OSL ages of the marine terrace sediments at Suryum fault site, using single grains of quartz, and briefly discuss their chronological implications on the timing of terrace formation along the southeastern coast of Korea. Of 1200 grains measured, 93 quartz grains were found to have OSL properties suitable for dating, the equivalent dose ($D_e$) values of which varied significantly, ranging from 50 Gy to 610 Gy with the overdispersion of $30{\pm}4%$. Applied to the Central Age Model (CAM) and Minimum Age Model (MAM), these quartz grains showed the OSL ages of $83{\pm}4ka$ and $60^{+3}{_{-7}}ka$, respectively, both of which are stratigraphically inconsistent with the previously reported OSL ages of lower $2^{nd}$ terrace (MIS 5a; ~80 ka). However, Finite Mixture Model (FMM) revealed that a small fraction of the measured quartz grains ($6{\pm}4%$) were of the ages ($194{\pm}24ka$) corresponding to MIS 7. Conclusively, based on single grain OSL ages, it would be prudent not to exclude the possibility that the marine terrace sediments at Suryum fault site have formed during MIS 7. Further, our single grain OSL ages imply that multiple grain(single aliquot) OSL dating methods are not applicable to the marine sediments at Suryum fault site.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.267-275
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• 2009

This paper presents the p-convergent coupling element on the basis of the ESSE(equivalent single layer shell element) and the PLLE(partial-linear layerwise element) to analyze laminated composite plates. The ESSE is formulated by the degenerated shell theory, on the other hand, the assumption of the PLLE is piecewise linear variation of the in-plane displacement and a constant value of lateral displacement across the thickness. The proposed finite element model is based on p-convergence approach. The integrals of Legendre polynomials and Gauss-Lobatto technique are chosen to interpolate displacement fields and to implement numerical quadrature, respectively. This study has been focused on the verification of p-convergent element. For this purpose, various finite element multiple models associated with the combination of ESSE and PLLE elements are tested to show numerical stability. The simple examples such as a cantilever beam subjected vertical load and a plate with tension are adopted to evaluate the performance of proposed element.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.406-412
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• 2001

In this paper, a new fuzzy single layer learning algorithm is proposed, which shows improved learning time and convergence property than that of the conventional fuzzy single layer perceptron algorithms. First, we investigate the structure of physiological neurons of the nervous system and propose new neuron structures based on fuzzy logic. And by using the proposed fuzzy neuron structures, the model and learning algorithm of Physiological Fuzzy Single Layer Perceptron(P-FSLP) are proposed. For the evaluation of performance of the P-FSLP algorithm, we applied the conventional fuzzy single layer perceptron algorithms and the P-FSLP algorithm to three experiments including Exclusive OR problem, the 3-bit parity bit problem and the recognition of car licence plates, which is an application of image recognition, and evaluated the performance of the algorithms. The experimentation results showed that the proposed P-FSLP algorithm reduces the possibility of local minima more than the conventional fuzzy single layer perceptrons do, and enhances the time and convergence for learning. Furthermore, we found that the P-FSLP algorithm has the great capability for image recognition applications.

• Journal of the Earthquake Engineering Society of Korea
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• v.4 no.2
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• pp.1-12
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• 2000

단층에 근접한 지진동에 대하여 성능이 저하되는 단자유도계의 변위응답에 대하여 연구하였다 5% 의 감쇠비를 갖는 세단계의 성능저하시스템을 5개의 단층에 근접한 지진동에 대하여 해석하였다 해석결과로부터 성능저하시스템의 비탄성 변위응답은 비저하시스템에 비하여 큰 값을 나타냄을 알 수 있었다 또한 성능저하 특성이 증가할수록 변위응답은 커지는 경향이 있다 이러한 변위증폭은 구조물의 고유주기 강도와 성능저하특성에 영향을 받으며 짧은 주기영역에서는 큰 값을 나타내며 긴 주기영역에서는 변위증폭이 거의 발생하지 않는다 단층에 근접한 각각의 지진동에 대한 변위증폭의 최대값은 1초 보다 작은 주기영역에서 비저하시스템의 4배 정도이다 변위증폭계수의 평균값은 짧은 주기영역에서는 2의 값을 가지면 구조물의 고유주기가 길어질수록 1에 수렴해 감을 알 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.479-484
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• 2005

본 논문에서는 오류 역전파 알고리즘에서 은닉층의 노드 수를 설정하는 문제와 ART1의 경계 변수의 설정에 따른 인식률이 저하되는 문제점을 개선하기 위해 ART1 알고리즘과 퍼지 단층 지도 학습 알고리즘을 결합한 ART1 기반 퍼지 지도 학습 알고리즘을 제안한다. 제안된 알고리즘은 가중치 조정에 승자 뉴런 방식을 도입하여 은닉층에 해당하는 클래스에 영향을 끼친 패턴들의 정보만 저장하게 하여 은닉층 노드로의 책임 분담에 의한 정체 현상이 일어날 가능성을 줄인다. 그리고 학습시간과 학습의 수렴성도 개선한다. 제안된 알고리즘의 학습 성능을 분석하기 위하여 주민등록번호 분류를 대상으로 실험한 결과, 제안된 방법이 기존의 신경망보다 경계 변수나 모멘트에 민감하지 않으며 학습 시간도 적게 소요되고 수렴성도 우수한 성능이 있음을 확인하였다.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.490-495
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• 1999

In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron structure. This method is applied to the XOR Problem, n bit parity problem which is used as the benchmark in neural network structure, and recognition of digit image in the vehicle plate image for practical image application. As a result of the experiments, it does not always guarantee the convergence. However, the network showed improved the teaming time and has the high convergence rate. The proposed network can be extended to an arbitrary layer Though a single layer structure Is considered, the proposed method has a capability of high speed 3earning even on large images.