• Geomechanics and Engineering
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• 제23권1호
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• pp.15-30
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• 2020

The probabilistic bearing capacity of a strip footing placed on the edge of a purely cohesive reinforced soil slope is computed by combining lower bound finite element limit analysis technique with random field method and Monte Carlo simulation technique. To simulate actual field condition, anisotropic random field model of undrained soil shear strength is generated by using the Cholesky-Decomposition method. With the inclusion of a single layer of reinforcement, dimensionless bearing capacity factor, N always increases in both deterministic and probabilistic analysis. As the coefficient of variation of the undrained soil shear strength increases, the mean N value in both unreinforced and reinforced slopes reduces for particular values of correlation length in horizontal and vertical directions. For smaller correlation lengths, the mean N value of unreinforced and reinforced slopes is always lower than the deterministic solutions. However, with the increment in the correlation lengths, this difference reduces and at a higher correlation length, both the deterministic and probabilistic mean values become almost equal. Providing reinforcement under footing subjected to eccentric load is found to be an efficient solution. However, both the deterministic and probabilistic bearing capacity for unreinforced and reinforced slopes reduces with the consideration of loading eccentricity.

• 대한전기학회논문지
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• 제40권6호
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• pp.551-561
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• 1991

The probabilistic generation simulation plays a key role in power system expansion and operational planning especially for the calculation of expected energy, loss of load probaility and unserved energy expected. However, it is crucial to develop a probabilistic generation simulation algorithm which gives sufficiently precise results within a reasonable computation time. In a previous paper, we have proposed an efficent method using Fast Hartley Transform in convolution process for considering the thermal and nuclear units. In this paper, a method considering the scheduling of pumped-storage plants and hydro plants with energy constraint is proposed. The method also adopts FHT techniques. We improve the model to include multi-state and multi-block generation. The method has been applied for a real size model system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권4호
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• pp.782-804
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• 2011

In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.1024-1029
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• 2010

The conventional factor of safety as used in geotechnical engineering does not reflect the degree of uncertainty of the relevant parameters. Then in the geotechnical engineering, there have been efforts to reflect the uncertainties of the geotechnical properties through probabilistic analysis. In this study, a practical method for calculation the second moment reliability index using the optimization tool of a spreadsheet software is introduced. And this methodology was proposed by Low, B. K.(1996). The method is based on the perspective of an ellipsoid that just touches the failure surface in the original space of the variables. The method is applied to vertical drains(PVD) and compared with th result of Monte Carlo Simulation method.

• 한국농공학회지
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• 제39권2호
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• pp.95-102
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• 1997

The technique of the calculation for probabilistic functions used in the reliability analysis of agricultural structures is proposed in this paper for adapting the standardization method using a numerical intergration. The proposed standardization method deals with the structures whose deviations of material properties and loads are large such that the deviation range from 20% to 70%. The results computed by the proposed method are compared with those obtained by the Monte Carlo Simulation. Deterministic values such as deflection, stress, obtained by conventional structural analysis can be directly changed to probabilistic distributions by the proposed method.

• Structural Engineering and Mechanics
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• 제21권5호
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• pp.507-518
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• 2005

In the shear-lag analysis of structures deterministic procedure is insufficient to provide complete information. Probabilistic analysis is a holistic approach for analyzing shear-lag effects considering uncertainties in structural parameters. This paper proposes an efficient and accurate algorithm to analyze shear-lag effects of structures with parameter uncertainties. The proposed algorithm integrated the advantages of the response surface method (RSM), finite element method (FEM) and Monte Carlo simulation (MCS). Uncertainties in the structural parameters can be taken into account in this algorithm. The algorithm is verified using independently generated finite element data. The proposed algorithm is then used to analyze the shear-lag effects of a simply supported beam with parameter uncertainties. The results show that the proposed algorithm based on the central composite design is the most promising one in view of its accuracy and efficiency. Finally, a parametric study was conducted to investigate the effect of each of the random variables on the statistical moment of structural stress response.

• 대한한의진단학회지
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• 제20권1호
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• pp.37-44
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• 2016

Ultrasonic imaging is the most widely modality among modern imaging device for medical diagnosis. Nevertheless, medical ultrasound images suffer from speckle noise and low contrast. In this paper, we propose probabilistic edge map for ultrasound image edge enhancement using automatic alien algorithm. The proposed method used applied speckle reduced ultrasound imaging for edge improvement using sequentially acquired ultrasound imaging. To evaluate the performance of method, the similarity between the reference and edge enhanced image was measured by quantity analysis. The experimental results show that the proposed method considerably improves the image quality with region edge enhancement.

• 한국지반공학회논문집
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• 제25권12호
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• pp.13-25
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• 2009

본 연구에서는 확률론적 해석에 지반의 공간적 변동성을 고려하기 위한 해석 절차를 제시하였다. 제안된 방법은 한계평형법을 이용하는 결정론적 해석방법을 지반정수의 불확실성과 공간적 변동성을 고려할 수 있도록 확률론적 사면안정 해석으로 확장한다. 개발된 방법은 랜덤유한요소해석법과 같이 미리 임계파괴면을 가정하지 않으면서도 계산시간을 단축할 수 있다는 장점이 있다. 지정된 입력 확률분포함수와 자기상관함수를 따르는 2차원의 랜덤필드를 생성하기 위하여 Karhunen-Lo$\grave{e}$ve 전개법을 사용하였으며, 생성된 랜덤필드를 이용하여 확률론적 응답을 얻기 위해 Monte Carlo 시뮬레이션을 수행하였다. 개발된 해석기법의 적용성을 검토하고 지반정수의 공간적 변화가 확률론적 안정해석에 미치는 영향을 검토하기 위해 예제해석을 수행하였으며, 해석결과는 제안된 방법이 지반물성의 공간적 변동성에 따른 다양한 사면파괴 형태를 확률론적 사면안정 해석에 효과적으로 고려할 수 있음을 보여준다.

• 전자공학회논문지B
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• 제28B권10호
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• 한국지반공학회논문집
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• 제18권5호
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• pp.271-280
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• 2002

본 연구에서는 사면안정해석 수행과정에서 입력되는 지반강도정수의 불확실성이 최소 신뢰성을 갖는 임계 활동면의 추적에 미치는 영향을 정량화하기 위한 확률론적 사면안정해석기법을 소개하였다. 일반적인 공사 현장에서 실무자가 상당한 양의 실내 및 현장 시험을 통해 얻어질 수 있는 지반강도정수의 다양한 통계.확률적 정보를 항상 확보하여 그것들을 상당한 수준의 통계적 지식을 가지고 자유스럽게 이용하는 것은 현실적으로 불가능하다. 따라서 본 연구에서는 실무자가 쉽게 확률적인 개념을 이해하면서 사면안정해석을 수행할 수 있도록 기존의 결정론적 사면안정해석 기법에 공학적 확률해석 기법을 결합시키는 방안을 제시하였다. 미 공병단에서 개발한 UTEXAS 3라는 범용 사면안정 해석 프로그램을 이용하여 본 연구는 파괴확률 또는 신뢰지수라는 관점에서 제안한 확률론적 사면안정해석기법의 결과들을 도출하였다. 본 확률론적 사면안정해석기법은 사면안정의 안전율만을 고려하는 기존의 결정론적 사면해석 기법들 보다 더욱 종합적으로 사면안정의 신뢰성에 대한 결과를 제시하는 것으로 나타났다.