• Title/Summary/Keyword: Probabilistic Method.

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Analysis of Landslide and Debris flow Hazard Area using Probabilistic Method in GIS-based (GIS 기반 확률론적 기법을 이용한 산사태 및 토석류 위험지역 분석)

  • Oh, Chae-Yeon;Jun, Kye-Won
    • Journal of the Korean Society of Safety
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    • v.27 no.6
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    • pp.172-177
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    • 2012
  • In areas around Deoksan Li and Deokjeon Li, Inje Eup, Inje Gun, located between $38^{\circ}2^{\prime}55^{{\prime}{\prime}}N$ and $38^{\circ}5^{\prime}50^{{\prime}{\prime}}N$ in latitude and $128^{\circ}11^{\prime}20^{{\prime}{\prime}}E$ and $128^{\circ}18^{\prime}20^{{\prime}{\prime}}E$ in longitude, large-sized avalanche disasters occurred due to Typhoon Ewiniar in 2006. As a result, 29 people were dead or missing, along with a total of 37.25 billion won of financial loss(Gangwon Province, 2006). To evaluate such landslide and debris flow risk areas and their vulnerability, this study applied a technique called 'Weight of Evidence' based on GIS. Especially based on the overlay analysis of aerial images before the occurrence of landslides and debris flows in 2005 and after 2006, this study extracted 475 damage-occurrence areas in a shape of point, and established a DB by using such factors as topography, hydrologic, soil and forest physiognomy through GIS. For the prediction diagram of debris flow and landslide risk areas, this study calculated W+ and W-, the weighted values of each factor of Weight Evidence, while overlaying the weighted values of factors. Besides, the diagram showed about 76% in prediction accuracy, and it was also found to have a relatively high correlationship with the areas where such natural disasters actually occurred.

Application of the French Codes to the Pressurized Thermal Shocks Assessment

  • Chen, Mingya;Qian, Guian;Shi, Jinhua;Wang, Rongshan;Yu, Weiwei;Lu, Feng;Zhang, Guodong;Xue, Fei;Chen, Zhilin
    • Nuclear Engineering and Technology
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    • v.48 no.6
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    • pp.1423-1432
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    • 2016
  • The integrity of a reactor pressure vessel (RPV) related to pressurized thermal shocks (PTSs) has been extensively studied. This paper introduces an integrity assessment of an RPV subjected to a PTS transient based on the French codes. In the USA, the "screening criterion" for maximum allowable embrittlement of RPV material is developed based on the probabilistic fracture mechanics. However, in the French RCC-M and RSE-M codes, which are developed based on the deterministic fracture mechanics, there is no "screening criterion". In this paper, the methodology in the RCC-M and RSE-M codes, which are used for PTS analysis, are firstly discussed. The bases of the French codes are compared with ASME and FAVOR codes. A case study is also presented. The results show that the method in the RCC-M code that accounts for the influence of cladding on the stress intensity factor (SIF) may be nonconservative. The SIF almost doubles if the weld residual stress is considered. The approaches included in the codes differ in many aspects, which may result in significant differences in the assessment results. Therefore, homogenization of the codes in the long time operation of nuclear power plants is needed.

Uncertainty Analysis for the Probabilistic Flood Forecasting (확률론적 홍수예측을 위한 불확실성 분석)

  • Lee, Kyung-Tae;Kim, Young-Oh;Kang, Tae-Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.71-71
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    • 2012
  • 현재 전 세계적으로 극한강우의 발생빈도가 점차 높아지고 있으며 홍수량 또한 강도가 커지고 있는 것이 현실이다. 하지만 과거의 홍수발생 빈도에 따라 설계된 홍수방어시설들이 점차 한계를 보이고 있으므로 이를 대비하기위한 구조적 대책뿐만 아니라 홍수피해 발생 가능지역에 사전 예경보를 시행하는 비구조적 대책마련 또한 필요하다. 기존의 홍수예측은 확정적인 하나의 유량예측값만을 제공함으로써 신속하고 편리하였지만 이에 대한 불확실성이 큰 경우 예상치 못한 큰 인적 물적 피해를 가져올 수 있다. 이처럼 확률론적 홍수예측의 필요성이 대두되어 지면서 유럽이나 미국등 선진국에서는 EFFS(European Flood Forecasting System)과 NWSRFS(National Water Service River Forecast System)같이 이미 확률론적 홍수예측에 대한 연구 및 기술개발이 활발하게 진행되어지고 있다. 하지만 홍수예측의 확률론적 접근에 있어서는 많은 불확실성들이 내포되어 있으므로 예측시스템에서 생성된 앙상블 유량예측 결과의 신뢰도 분석과 올바른 불확실성 정보의 제공이 필요하다. 본 연구는 확률론적 홍수예측 방법을 국내에 적용시켜서 기상청의 예측시스템 KLAPS(Korea Local Analysis and Prediction System), MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation), UM(Unified Model) 그리고 MOGREPS(Met Office Global Regional Ensemble Prediction System)으로부터 생성된 기상앙상블을 현재 국토해양부 홍수통제소에서 사용하고 있는 강우-유출모형인 저류함수모형(Storage Function Method)의 입력 자료로 사용한다. 확률론적 홍수예측에서 오는 불확실성을 분석하기 위해서 첫 번째로 제공되는 기상예측 시스템의 시 공간적 스케일 및 대상유역의 공간특성에 따라 어떠한 형태로 전파되어지는지를 분석하였다. 두 번째는 각각의 예측시스템들이 선행기간(Lead time)에 따라 불확실성의 특성이 어떻게 나타나게 되는지를 확인하였다. 이러한 불확실성의 특성을 정확하게 파악하게 된다면 예측에 있어서 현재 갖고 있는 문제점들로부터 개선해 나가야 할 방향을 제시해주어 향후연구에 유용하게 활용될 수 있을 것이다.

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Hardness Evaluation of Spot Welding Using Instrumented Indentation Technique (계장화 압입시험법을 이용한 점용접부의 경도평가)

  • Jin, Ji-Won;Kwak, Sung-Jong;Yoo, Dong-Ok;Kim, Tae-Seong;Kang, Ki-Weon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.9
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    • pp.1081-1086
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    • 2012
  • This study deals with hardness evaluation for spot welding by using an instrumented indentation technique to improve the quality of the inspection methodology. First, an instrumented indentation test and a Rockwell hardness test were performed for normal and abnormal spot welding. The hardness to indentation force-displacement curve obtained using each of the tests was compared. Furthermore, an analysis was conducted using the hardness obtained by the instrumented indentation technique. A quality control standard based on reliability was this evaluated for spot welding.

Use of Drug-eluting Stents Versus Bare-metal Stents in Korea: A Cost-minimization Analysis Using Population Data

  • Suh, Hae Sun;Song, Hyun Jin;Jang, Eun Jin;Kim, Jung-Sun;Choi, Donghoon;Lee, Sang Moo
    • Journal of Preventive Medicine and Public Health
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    • v.46 no.4
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    • pp.201-209
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    • 2013
  • Objectives: The goal of this study was to perform an economic analysis of a primary stenting with drug-eluting stents (DES) compared with bare-metal stents (BMS) in patients with acute myocardial infarction (AMI) admitted through an emergency room (ER) visit in Korea using population-based data. Methods: We employed a cost-minimization method using a decision analytic model with a two-year time period. Model probabilities and costs were obtained from a published systematic review and population-based data from which a retrospective database analysis of the national reimbursement database of Health Insurance Review and Assessment covering 2006 through 2010 was performed. Uncertainty was evaluated using one-way sensitivity analyses and probabilistic sensitivity analyses. Results: Among 513 979 cases with AMI during 2007 and 2008, 24 742 cases underwent stenting procedures and 20 320 patients admitted through an ER visit with primary stenting were identified in the base model. The transition probabilities of DES-to-DES, DES-to-BMS, DES-to-coronary artery bypass graft, and DES-to-balloon were 59.7%, 0.6%, 4.3%, and 35.3%, respectively, among these patients. The average two-year costs of DES and BMS in 2011 Korean won were 11 065 528 won/person and 9 647 647 won/person, respectively. DES resulted in higher costs than BMS by 1 417 882 won/person. The model was highly sensitive to the probability and costs of having no revascularization. Conclusions: Primary stenting with BMS for AMI with an ER visit was shown to be a cost-saving procedure compared with DES in Korea. Caution is needed when applying this finding to patients with a higher level of severity in health status.

An Extended Generative Feature Learning Algorithm for Image Recognition

  • Wang, Bin;Li, Chuanjiang;Zhang, Qian;Huang, Jifeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.3984-4005
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    • 2017
  • Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

On Mathematical Representation and Integration Theory for GIS Application of Remote Sensing and Geological Data

  • Moon, Woo-Il M.
    • Korean Journal of Remote Sensing
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    • v.10 no.2
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    • pp.37-48
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    • 1994
  • In spatial information processing, particularly in non-renewable resource exploration, the spatial data sets, including remote sensing, geophysical and geochemical data, have to be geocoded onto a reference map and integrated for the final analysis and interpretation. Application of a computer based GIS(Geographical Information System of Geological Information System) at some point of the spatial data integration/fusion processing is now a logical and essential step. It should, however, be pointed out that the basic concepts of the GIS based spatial data fusion were developed with insufficient mathematical understanding of spatial characteristics or quantitative modeling framwork of the data. Furthermore many remote sensing and geological data sets, available for many exploration projects, are spatially incomplete in coverage and interduce spatially uneven information distribution. In addition, spectral information of many spatial data sets is often imprecise due to digital rescaling. Direct applications of GIS systems to spatial data fusion can therefore result in seriously erroneous final results. To resolve this problem, some of the important mathematical information representation techniques are briefly reviewed and discussed in this paper with condideration of spatial and spectral characteristics of the common remote sensing and exploration data. They include the basic probabilistic approach, the evidential belief function approach (Dempster-Shafer method) and the fuzzy logic approach. Even though the basic concepts of these three approaches are different, proper application of the techniques and careful interpretation of the final results are expected to yield acceptable conclusions in cach case. Actual tests with real data (Moon, 1990a; An etal., 1991, 1992, 1993) have shown that implementation and application of the methods discussed in this paper consistently provide more accurate final results than most direct applications of GIS techniques.

Probabilistic Runoff Analysis using Ensemble Technoque with Localization Method (앙상블 기반 지역화 기법을 이용한 확률론적 유출량 분석)

  • Lee, Han-Yong;Jang, Suk-Hwan;Lee, Jae-Kyoung;Jo, Jun-Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.207-207
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    • 2019
  • 최근 우리나라는 지역 특성 및 기후변화의 영향으로 인해 수문학적 요소의 변동성이 커지고 수자원의 지속적인 관리에 있어 유출량은 중요한 문제로 여겨지고 있다. 특히 일부 소하천 또는 접경지역과 같은 미계측유역은 수문학적 요소에 대한 자료가 부족하고 수문모형의 초기치 설정과 과거 유출량 자료를 통하여 최적화한 매개변수를 결정해야하므로 장기유출분석이 어렵다. 본 연구의 적용유역으로 미계측유역인 임진강상류 유역에 대한 유출량 추정을 위해 계측 유역의 자료를 활용하여 모형의 매개변수 등을 추정하는 지역화 기법인 다중선형회귀분석과 공간근접분석을 활용하여 유출량을 산정 및 검증하였다. 또한, 확률론적 예측이 가능한 앙상블 기법 적용을 통한 유출량 예측을 하였고, 이를 예측 정확성 평가지표를 통해 효율성 검토를 수행하여 미계측유역의 유출량에 대해 확률론적 예측을 수행하였다. 대표적 지역화 기법의 적용성을 검토한 결과, 계측유역을 통해 다중선형회귀분석과 공간근접분석을 abcd 모형에 적용하였다. 모의유출량을 산정하고 실측 유출량과 비교 분석 결과 모의정확성이 높게 분석되었다. 이와 같은 검증 결과를 토대로 미계측유역의 유출량을 추정하였다. 또한, 지역화 기법을 앙상블 기법에 적용하여 확률론적 유출량 예측의 효율성을 검토하였다. 적용유역과 같은 지류를 포함하고 있는 임진강하류 유역을 대상으로 수행하였다. 검증기간(2013년~2017년) 동안의 월 예측 유출량 앙상블 생성을 위해 과거 강우량와 증발량(1988년~2012년) 자료를 사용하였으며, 지역화 기법을 적용한 abcd 모형을 이용하였다. 예측 유출량의 정확성 평가를 실시하였으며, 정확성이 비교적 높게 분석되었다. 이와 같은 결과를 토대로 미계측유역의 확률론적 유출량을 예측하였다. 따라서, 대표적 지역화 기법을 앙상블 기법에 적용하여 확률론적 유출량을 예측할 경우 보다 정확한 유출량 예측이 가능하다.

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Estimating uncertainty in limit state capacities for reinforced concrete frame structures through pushover analysis

  • Yu, Xiaohui;Lu, Dagang;Li, Bing
    • Earthquakes and Structures
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    • v.10 no.1
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    • pp.141-161
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    • 2016
  • In seismic fragility and risk analysis, the definition of structural limit state (LS) capacities is of crucial importance. Traditionally, LS capacities are defined according to design code provisions or using deterministic pushover analysis without considering the inherent randomness of structural parameters. To assess the effects of structural randomness on LS capacities, ten structural parameters that include material strengths and gravity loads are considered as random variables, and a probabilistic pushover method based on a correlation-controlled Latin hypercube sampling technique is used to estimate the uncertainties in LS capacities for four typical reinforced concrete frame buildings. A series of ten LSs are identified from the pushover curves based on the design-code-given thresholds and the available damage-controlled criteria. The obtained LS capacities are further represented by a lognormal model with the median $m_C$ and the dispersion ${\beta}_C$. The results show that structural uncertainties have limited influence on $m_C$ for the LSs other than that near collapse. The commonly used assumption of ${\beta}_C$ between 0.25 and 0.30 overestimates the uncertainties in LS capacities for each individual building, but they are suitable for a building group with moderate damages. A low uncertainty as ${\beta}_C=0.1{\sim}0.15$ is adequate for the LSs associated with slight damages of structures, while a large uncertainty as ${\beta}_C=0.40{\sim}0.45$ is suggested for the LSs near collapse.

Probabilistic Object Recognition in a Sequence of 3D Images (연속된 3차원 영상에서의 통계적 물체인식)

  • Jang Dae-Sik;Rhee Yang-Won;Sheng Guo-Rui
    • KSCI Review
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    • v.14 no.1
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    • pp.241-248
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    • 2006
  • The recognition of a relatively big and rarely movable object. such as refrigerator and air conditioner, etc. is necessary because these objects can be crucial global stable features of Simultaneous Localization and Map building(SLAM) in the indoor environment. In this paper. we propose a novel method to recognize these big objects using a sequence of 3D scenes. The particles representing an object to be recognized are scattered to the environment and then the probability of each particles is calculated by the matching test with 3D lines of the environment. Based on the probability and degree of convergence of particles, we can recognize the object in the environment and the pose of object is also estimated. The experimental results show the feasibility of incremental object recognition based on particle filtering and the application to SLAM

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