• Journal of the Korean GEO-environmental Society
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• v.10 no.5
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• pp.49-57
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• 2009

In this study, one of the complicated geotechnical problem, compression index was predicted by a artificial neural network method of Levenberg-Marquardt (LM) algorithm. Predicted values were compared and evaluated by the results of the Back Propagation (BP) method, which is used extensively in geotechnical engineering. Also two different results were compared with experimental values estimated by verified experimental methods in order to evaluate the accuracy of each method. The results from experimental method generally showed higher error than the results of both artificial neural network method. The predicted compression index by LM algorithm showed better comprehensive results than BP algorithm in terms of convergence, but accuracy was similar each other.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.44-45
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• 2019

최근 CNN 등 인공신경망은 최근 이미지 분류, 객체 인식, 자연어 처리 등 다양한 분야에서 뛰어난 성능을 보이고 있다. 그러나, 대부분의 분야에서 보다 더 높은 성능을 얻기 위해 사용한 인공신경망 모델들은 파라미터 수 및 연산량 등이 방대하여, 모바일 및 IoT 디바이스 같은 연산량이나 메모리가 제한된 환경에서 추론하기에는 제한적이다. 따라서 연산량 및 모델 파라미터 수를 압축하기 위한 딥러닝 경량화 알고리즘이 연구되고 있다. 본 논문에서는 임베디트 보드에서의 압축된 CNN 모델의 성능을 검증한다. 인공지능 지원 맞춤형 칩인 QCS605 를 내장한 임베디드 보드에서 카메라로 입력한 영상에 대해서 원 CNN 모델과 압축된 CNN 모델의 분류 성능과 동작속도 비교 분석한다. 본 논문의 실험에서는 CNN 모델로 MobileNetV2, VGG16 을 사용했으며, 주어진 모델에서 가지치기(pruning) 기법, 양자화, 행렬 분해 등의 인공신경망 압축 기술을 적용하였을 때 원래의 모델 대비 추론 시간 및 분류의 정확도 성능을 분석하고 인공신경망 압축 기술의 유용성을 확인하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.293-303
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• 2011

An efficient diagonalized approximate factorization algorithm (DAF) is developed for the solution of three-dimensional incompressible viscous flows. The pressure-based, artificial compressibility (AC) method is used for calculating steady incompressible Navier-Stokes equations. The AC form of the governing equations is discretized in space using a second-order-accurate finite volume method. The present DAF method is applied to derive a second-order accurate splitting of the discrete system of equations. The primary objective of this study is to investigate the computational efficiency of the present DAF method. The solutions of the DAF method are evaluated relative to those of well-known four-stage Runge-Kutta (RK4) method for fully developed and developing laminar flows in curved square ducts and a laminar flow in a cavity. While converged solutions obtained by DAF and RK4 methods on the same computational meshes are essentially identical because of employing the same discrete schemes in space, both algorithms shows significant discrepancy in the computing efficiency. The results reveal that the DAF method requires substantially at least two times less computational time than RK4 to solve all applied flow fields. The increase in computational efficiency of the DAF methods is achieved with no increase in computational resources and coding complexity.

• Journal of the Korean Geotechnical Society
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• v.24 no.11
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• pp.111-120
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• 2008

The characteristic of induced anisotropy is investigated in this study for the Pohang mudstone involving the cut plane discontinuity. The uniaxial and triaxial compression tests are performed for anisotropic rocks with artificial joint to look into anisotropic strength characteristics. Both the uniaxial compressive strength and triaxial compressive strength show the lowest value at the angle of cut plane, ${\beta}=30^{\circ}$ and the shoulder type of anisotropy is obtained. Anisotropy ratio (Rc) in uniaxial compression measures 9.0, whereas Rc=1.29-1.98 in triaxial compression is appeared. A series of analyses are made with the test results to derive the suitable parameter values when it is applied to the Ramamurthy (1985) failure criterion. The result of uniaxial compression test is analyzed by introducing the n-index into Ramamurthy failure criterion. The result shows that, n=l is suitable for ${\beta}=0^{\circ}{\sim}30^{\circ}$ and n=3 is suitable for ${\beta}=30^{\circ}{\sim}90^{\circ}$. To analyze the result of triaxial compression test by Ramamurthy failure criterion, anisotropy ratio in uniaxial compression test is added to Ramamurthy's equation and material constants are estimated by modified Ramamurthy's equation. When these values are applied back to Ramamurthy failure criterion, the predicted values are well fitted to the test results. And strength anisotropy for failure criteria of Jaeger (1960), McLamore & Gray (1967) and Hoek & Brown (1980) are also investigated.

• Journal of the Korean Geotechnical Society
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• v.17 no.6
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• pp.25-36
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• 2001

The purpose of this paper is to discuss the effects of soil properties such as liquid limit, water content, etc. on the compression index and to propose the empirical equation of compression index far regional clay and to verify the application Back Propagation Neural Network(BPNN). The compression index values obtained from laboratory tests are in the range of 0.01 to 3.06 for clay soils sampled in eleven regions. As the compare with the results of laboratory test and the predicted compression index value from the proposed empirical equations, the results of empirical equations including single soil parameter have a possibility to be overestimated. Also, the results of empirical equations including multiple soil parameters closed to the measured value more than that of empirical equations including single soil parameter, but the standard error for measured value obtained larger than 0.05. For these reasons, the empirical equations including single or multiple soil parameters proposed base on the results of laboratory test and the determination coefficient is up to 0.89. The result of BPNN shows that correlation coefficient and standard error between test and neural network result is larger than 0.925 and smaller than 0.0196, which means high correlativity, respectively. Especially, the estimated result by neural network, using only three parameters such as natural water content, dry unit weight and in-situ void ratio among various factors is available to the estimation of compression index and the correlation coefficient is 0.974. This result verified the possibility that if BPNN use, the compression index can be predicted by the parameters, which obtained from simplex field test.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.151-154
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• 2020

뉴럴넷 기술이 발전과 힘께 다양한 분야에서 획기적인 성능 향상이 이루어지고 있다. 이미지 압축 분야에서도 기존의 전통적인 툴 제인 구조의 압축 방식에서 벗어나 종단간(end-to-end) 뉴렬넷 기반의 이미지 압축 기술에 대한 연구가 활발히 이루어지고 있다. 특히 최근 네트워크를 통해 변환된 피쳐 데이터의 엔트로피를 최소화하는 방식에 대한 연구가 활발히 이루어지고 있으며, 이에 기반한 최근의 연구는 VVC 화면 내 코딩 기술보다 우수한 코딩 효율성을 제공하고 있다. 그러나 변환된 피쳐 데이터에 대한 특성 분석은 부족한 실정이며, 이에 본 논문에서는 엔트로피 최소화 기반 종단간 이미지 압축 네트워크의 피쳐 공간 데이터에 대한 공간적 (spatial) 상관관계와 채널간(inter-channel) 상관관계(correlation)를 분석하고, 나아가 최근 제안된 종단간 이미지 압축 네트워크의 문맥 기반 예측 기능을 통해 잔존하는 데이터 중복성이 효과적으로 제거됨을 보인다.

• Journal of the Korean Geotechnical Society
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• v.27 no.1
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• pp.17-24
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• 2011

The characteristics of flow and strength of CLSM depend on the combination ratio including the fly ash, pond ash, cement, water quantity and etc. However, it is very difficult to draw the mechanism about the flow, strength and the mixing ratio of each components. Therefore, the method of calculation drawing the flow about the component ratio of CLSM and compression strength value is needed for the valid practical use of CLSM. To verify the efficiency of artificial neural network, new data which were not used for establishing the model were predicted and compared with the results of laboratory tests. In this research, it was used to evaluate the learning efficiency of the artificial neural network model and the prediction ability by changing the node number of hidden layer, learning rate, momentum, target system error and hidden layer. By using the results, the optimized artificial neural network model which is suitable for a flow and compressive strength estimate of CLSM was determined.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.146-149
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• 2022

기존 RDO(Rate Distortion Optimization) 기반 압축 방식은 압축 성능에 초점을 두기 때문에 영상 내 인지 특성이 무시될 수 있다. 따라서 RoI(Region of Interest)을 기반으로 압축률을 조절하는 연구가 고안[1, 2, 3, 4] 되었으며, HVS(Human Visual System) 관점에서 영상 내 중요한 부분에 대해 더 높은 품질로 영상을 압축하는 연구가 대부분이다. 최근 인공지능 기술이 발전함에 따라 지능형 영상 분석에 대한 수요가 증가하고 있으며, 이에 따라 머신 비전을 위한 영상 부호화 및 효율적인 전송에 대한 필요성이 대두되고 있다. 본 논문에서는 VVC(Versatile Video Coding)의 dQP(delta Quantization Parameter)를 활용하여 RoI(Region of Interest) 기반압축 방법을 제안하고, 두가지의 RoI 추출 방식을 소개한다. Detectron2 Faster R-CNN X101-FPN [5]의 첫번째 탐지기를 통해 후보 영역 기반 RoI 을 추출하고, 두번째 탐지기를 통해 객체 기반 RoI 을 추출하여, 영상 내 객체 부분과 비객체 부분으로 나누어 서로 다른 압축률로 압축을 수행하였으며, 이에 따른 성능을 비교하고자 한다.

• Journal of computational fluids engineering
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• v.4 no.1
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• pp.41-52
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• 1999

이 논문에서는, QUICK해법의 불안정성을 개량하므로써, 수치계산에 있어서 수렴이 빠르고, 수치적으로 안정한 계산을 할 수 있는 새로운 MQUICK 상류해법을 제안하고, 이를 비압축성 층류유동의 계산에 적용하였다. 또한, 해법의 정확성, 안정성, 수렴속도에 대한 검토를 통하여 본 MQUICK 상류해법의 유효성과 타당성이 평가되었다. 이 해법에서는 인공산일의 가감을 조절하기 위하여 가중계수 α를 써서 정식화 하였고, 위의 검토를 통하여 α의 최적값을 조사하였다. 이 해법을 SMAC 음해법에 적용하여 2 차원 공동유동, 3 차원 덕트유동과 같은 몇몇 표준문제를 계산하고, 계산된 결과를 실험값 또는, 3 차 정확도의 상류해법 및 QUICK해법에 의한 결과 들과 비교 하므로써, 본 MQUICK 상류해법이 위의 다른 해법에 비하여 안정하고, 유효성이 높은 해법임을 확인 하였다.

• Korean Journal of Agricultural Science
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• v.23 no.1
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• pp.39-50
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• 1996

The normal cement concrete is widely used material to build the construction recently, but it has a fault to increase the dead load on account of its unit weight is large compared with strength. So, many engineers are continuously searching for new materials of construction to provide greater performance at lower density. Many studies were carried out on the lightweight aggregate concrete in foreign country in the latter half of the 19th century, therefore lightweight aggregate concrete has been used successfully for many years for structural members. The main purpose of the work described in this paper were to establish its physical and mechanical properties of no-fines lightweight concrete using synthetic lightweight coarse aggregates. Test results are summarized as follows ; The water-cement ratio was shown less than 33% in use synthetic lightweight coarse aggregates, unit weights of synthetic lightweight concrete was shown less than $1,800kg/m^3$ and compressive strength was higher than $200kg/m^2$. And the pulse velocity was more than 3,000m/sec. The relationship of compressive strength between unit weight and pulse velocity was shown to be approximately linear.