• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.109-125
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• 2004

In recent decades, microscopic simulation models have become powerful tools to analyze traffic flow on highways and to assist the investigation of level of service. The existing microscopic simulation models simulate an individual vehicle's speed based on a constant free-flow speed dominantly specified by users and driver's behavior models reflecting vehicle interactions, such as car following and lane changing. They set a single free-flow speed for a single vehicle on a given link and neglect to consider the effects of highway design elements to it in their internal simulation. Due to this, the existing models are limitted to provide with identical simulation results on both curved and tangent sections of highways. This paper presents a model developed to estimate the change of free-flow speeds based on highway design elements. Nine neural network models were trained based on the field data collected from seven different freeway curve sections and three different locations at each section to capture the percent changes of free-flow speeds: 100 m upstream of the point of curve (PC) and the middle of the curve. The model employing seven highway design elements as its input variables was selected as the best : radius of curve, length of curve, superelevation, the number of lanes, grade variations, and the approaching free-flow speed on 100 m upstream of PC. Tests showed that the free-flow speeds estimated by the proposed model were statistically identical to the ones from the field at 95% confidence level at each three different locations described above. The root mean square errors at the starting and the middle of curve section were 6.68 and 10.06, and the R-squares at these points were 0.77 and 0.65, respectively. It was concluded from the study that the proposed model would be one of the potential tools introducing the effects of highway design elements to free-flow speeds in simulation.

• Journal of the Korean Geotechnical Society
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• v.21 no.8
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• pp.73-84
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• 2005

A three layered neural network model was developed using back propagation algorithm to estimate the UU undrained shear strength of Korean soft soil based on the database of actual undrained shear strengths and piezocone measurements compiled from 8 sites over the Korea. The developed model was validated by comparing model predictions with measured values about new piezocone data, which were not previously employed during development of model. Performance of the neural network model was also compared with conventional empirical methods. It was found that the number of neuron in hidden layer is different for the different combination of transfer functions of neural network models. However, all piezocone neural network models are successful in inferring a complex relationship between piezocone measurements and the undrained shear strength of Korean soft soils, which give relatively high coefficients of determination ranging from 0.69 to 0.72. Since neural network model has been generalized by self-learning from database of piezocone measurements and undrained shear strength over the various sites, the developed neural network models give more precise and generally reliable undrained shear strengths than empirical approaches which still need site specific calibration.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.49-58
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• 2012

This study estimates the flexural behavior of reinforced recycled aggregate concrete beams. Three specimens with different types and water absorption of coarse aggregates were constructed and tested. Not only all specimens were designed to be subjected to 4-point concentrated loads, but also the shear span-to-depth ratio of 2.5 was adjusted to all specimens to increase the effect of shear. A nonlinear flexural analysis considering the tension stiffening effect of concrete was performed to predict the moment versus curvature relationships of the specimens. Furthermore, a nonlinear finite element analysis considering the effect of shear was carried out to estimate the behavior of the specimens. It can be found from experimental results that the flexural strength and the crack properties of the specimens with recycled coarse aggregate having a water absorption of 6% were similar to those of the specimen with natural aggregates. The comparison between the experimental and analytical results showed that existing analytical methods can be successfully used to predict the behavior of reinforced recycled aggregate concrete beams.

• Journal of the Earthquake Engineering Society of Korea
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• v.14 no.5
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• pp.41-51
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• 2010

For safe seismic evaluation and design, it is necessary to predict the plastic deformation demands of members. In the present study, a quick and reasonable method for the evaluation of member plastic deformations of dual systems was developed on the basis of results of elastic analysis, without using nonlinear analysis. Plastic deformations of beams, columns, and walls are functions of member stiffness, story drift ratio, and moment redistribution determined from elastic analysis. For dual systems with rigid connections between walls and beams, an increase in the plastic deformations of beams due to the rocking effect was considered. The proposed method was applied to 8-story dual systems and the predicted plastic deformations were compared with the results of nonlinear analysis. The results showed that the proposed method accurately predicted the member plastic deformations with simple calculations, but that for the accurate evaluation of member plastic deformations, the inelastic story drift ratio must also be predicted with accuracy. The proposed method can be applied to both the performance-based seismic design of new structures and the seismic evaluation of existing structures.

• Journal of Korean Society of Steel Construction
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• v.19 no.5
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• pp.503-513
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• 2007

The seismic responses of a building are affected by the connection characteristics that have effects on structural stiffness. In this study, push-over analysis and time history analysis were performed to estimate structural behavior of 2D eight-story unbraced steel structures with partially restrained composite connections using a nonlinear dynamic analysis program. Nonlinear $M-{\theta}$characteristics of connection and material inelastic characteristics of composite beam and steel column were considered. The idealization of composite semi-rigid connection as fully rigid connection yielded an increase in initial stiffness and ultimate strength in the push-over analysis. In time history analysis, the stiffness and hysteretic behavior of connections have effects on base-shear force, maximum story-drift and maximum moment in beams and columns. For seismic waves with PGA of 0.4 g, the structure with the semi-rigid composite connections shows the maximum story-drift with less than the life safety criteria by FEMA 273 and no inelastic behavior of beam and column, whereas in the structure with rigid connections, beams and columns have experienced inelastic behaviors.

• ICROS
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• v.3 no.5
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• pp.38-42
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• 1997

본 고에서는 적응제어의 설계 기법의 연구 현황에 대해 살펴보았다. 매개변수 추정을 기반으로 적응제어기 설계 기법(Estimation-based Design Technique)은 자기동조제어를 시작으로 적응 최적제어 단계를 거쳐, 현재 다변수 적응예측제어로 발전하였고, 이는 화학공정 등 실제 플랜트에 응용될 가능성이 가장 높은 실용적인 설계기법으로 평가받고 있다. 그러나 비선형 시스템에 대한 적용 연구는 활발하지 못한 형편이다. 한편, 안정도 이론을 기반으로 적응 메카니즘을 설계하는 연구는 선형 시스템에 대한 적응제어 연구로 확장되어 현재 활발한 연구가 진행되고 있다. 앞으로 이에 대한 이론 연구가 한동안 지속될 것으로 전망된다. 그러나 이 방법은 실제 시스템에 적용시 적합한 형태로 불확실성을 모델링해야 하며 그 작업은 그리 용이하지 않을 것으로 판단된다. 그러나 부분적으로 이러한 응용연구에 대한 노력이 경주되어야 할 것이다. 비매개변수 추정방법은 적응제어 이론의 주 설계기법은 아니기 때문에 이론으로의 확장 연구는 그리 활발하지 못한 것으로 판단된다. 그러나 비교적 설계방법과 불확실성 모델링이 간단하여 실제 응용에 가장 용이하게 적용될 수 있을 것으로 생각된다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2016.11a
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• pp.201.1-201.1
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• 2016

전주된 Invar (Fe-35%Ni) 박판 위에 증착된 Cu 박막은 스퍼터 전력량이 증가할수록 증착속도가 증가하였다. Cu/Invar 박판이 Invar 박판보다 면저항 값이 34%로 작았다. Invar 박판 위에 Cu가 증착되면 최대자화와 투자율은 각각 40.3, 65.0 [%] 감소하였다. Cu 박막의 탄성하강강성도, 마찰계수, 피로한계는 각각 45, 0.130, 0.093 이었다. 동적 나노 압침법으로 얻은 Invaar/Cu 박막의 하중-시간-변위 곡선의 가장 큰 차이는 탄성하강강성도(elastic stiffness) 이었다. 미세경도와 나노경도의 실험적 관계식은 $Y[GPa]=9.18{\times}10^{-3}X[Hv]$ 이었다. 나노압침선단의 하중분포를 이차원 선형 및 비선형 유한요소해석을 통하여 1.0 [mN] 의 정적하중을 가한 Cu 박막은 486 [mN] 으로 예측되었다. 이는 표면탐침현미경으로 관찰한 압흔의 변형정도와 유사한 경향을 보였다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.4 no.3
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• pp.156-160
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• 1992

The evolution of leading waves generated by a wavemaker in a two-dimensional tank has been studied. The front of wave trains can be described in general by the Schrodinger equation. In particular, when the slope of the carrier waves is steep, and hence nonlinearity becomes important, the cubic Schrodinger equation is proved to be an appropriate mathematical model. Computations are made by using the Crank-Nicolson algorithm and compared with experimental data. It is found that the numerical result predicts the evolution of leading waves fairly well and the evolution is significantly affected by nonlinearity for steep waves when kh＞1.36.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.467-470
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• 2004

퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화 될 필요성이 요구된다. 일반적으로, 정보 granules는 근접성, 유사성 또는 기능성 등에 인하여 서로 결합되는 요소(특히, 수치 데이터)의 실체이다. 본 논문에서는 비선형 시스템의 퍼지모델을 위해 정보 granules에 의한 퍼지 관계 기반 퍼지 추론 시스템을 최적 설계한다. 제안된 퍼지 모델은 정보 데이터의 특성을 살리기 위해 HCtl 클러스터링 방법에 의한 중심값을 이용하여 모든 입력변수가 상호 관계한 전반부/후반부 구조 및 파라미터 동정을 시행한다. 두 가지 형태의 퍼지 추론 방법은 간략 추론과 선형추론에 의해 수행되고 삼각형 멤버쉽 함수를 사용한다. 구축된 정보 granule 기반 퍼지 모델은 유전자 알고리즘을 이용하여 전반부 파라미터를 최적으로 동정한다. 그리고 학습 및 테스트 데이터의 성능 결과의 상호균형을 얻기 위한 하중값을 가진 성능지수를 사용하여 근사화와 예측성능의 향상을 꾀하며, 기존 문헌과의 성능비교를 통해 제안된 퍼지 모델을 평가한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.44-45
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• 2017

본 논문에서는 비균등 선형 마이크로폰 어레이를 활용한 convolutional neural network (CNN) 기반의 음원분리 방법을 제안한다. 우선, 주어진 어레이 배치에 따라 채널간의 시간차를 분석하고, 분석된 시간차에 따라 주파수별로 방사각과 넓이에 따라 입력 오디오 신호의 spectral magnitude를 예측한다. 그러고 나서, CNN 분류기로부터 최적의 방사각과 넓이를 선별하고 이를 통해 음원을 분리한다.