• 제목/요약/키워드: Expectation Maximization

검색결과 222건 처리시간 0.025초

의료서비스에서 혼합모형(Mixture model) 및 분석적 계층과정(AHP)를 이용한 입원환자의 시장세분화에 관한 연구 (Segmenting Inpatients by Mixture Model and Analytical Hierarchical Process(AHP) Approach In Medical Service)

  • 백수경;곽영식
    • 보건행정학회지
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    • 제12권2호
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    • pp.1-22
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    • 2002
  • Since the early 1980s scholars have applied latent structure and other type of finite mixture models from various academic fields. Although the merits of finite mixture model are well documented, the attempt to apply the mixture model to medical service has been relatively rare. The researchers aim to try to fill this gap by introducing finite mixture model and segmenting inpatients DB from one general hospital. In section 2 finite mixture models are compared with clustering, chi-square analysis, and discriminant analysis based on Wedel and Kamakura(2000)'s segmentation methodology schemata. The mixture model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture model is to unfix the sample, to Identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. In section 3 and 4 we illustrate results of segmenting 4510 patients data including menial and ratio scales. And then, we show AHP can be identify the attractiveness of each segment, in which the decision maker can select the best target segment.

위성 안개 영상을 위한 강인한 특징점 검출 기반의 영상 정합 (Image Matching Based on Robust Feature Extraction for Remote Sensing Haze Images)

  • 권오설
    • 방송공학회논문지
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    • 제21권2호
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    • pp.272-275
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    • 2016
  • 본 논문은 위성 영상을 위한 안개 제거 및 표면반사율 기반의 특징점 검출 방법을 제안한다. 기존의 안개 제거를 위한 DCP 방법은 패치 기반의 처리 방식으로 인해 전달맵 생성 과정에서 블록현상이 발생하게 되고, 이는 영상을 흐리게 하는 원인이 된다. 따라서 제안한 은닉마코프 기반의 방법은 영상의 블록 현상을 제거하고 선명도를 향상한다. 또한 표면반사율 기반의 견고한 특징점 추출을 통해서 영상 정합의 정확성을 향상하였다. 실험을 통해 제안한 방법이 기존 방법에 비해 안개 제거의 성능에서 우수함을 확인하였으며 이를 통해 특징 검출 및 위성 영상 정합에 적합함을 확인하였다.

Novel Partitioning Algorithm for a Gaussian Inverse Wishart PHD Filter for Extended Target Tracking

  • Li, Peng;Ge, Hongwei;Yang, Jinlong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권11호
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    • pp.5491-5505
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    • 2017
  • Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

계층적 클러스터링과 Gaussian Mixture Model을 이용한 뉴로-퍼지 모델링 (A Neuro-Fuzzy Modeling using the Hierarchical Clustering and Gaussian Mixture Model)

  • 김승석;곽근창;유정웅;전명근
    • 한국지능시스템학회논문지
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    • 제13권5호
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    • pp.512-519
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    • 2003
  • 본 논문에서는 계층적 클러스터링과 GMM을 순차적으로 이용하여 최적의 파라미터를 추정하고 이를 뉴로-퍼지 모델의 초기 파리미터로 사용하여 모델의 성능 개선을 제안한다. 반복적인 시도 중 가장 좋은 파라미터를 선택하는 기존의 알고리즘 과 달리 계층적 클러스터링은 데이터들 간의 유클리디언 거리를 이용하여 클러스터를 생성하므로 반복적인 시도가 불필요하다. 또한 클러스터링 방법에 의해 퍼지 모델링을 행하므로 클러스터와 동일한 갯수의 적은 규칙을 갖는다. 제안된 방법의 유용함을 비선형 데이터인 Box-Jenkins의 가스로 예측 문제와 Sugeno의 비선형 시스템에 적용하여 이전의 연구보다 적은 규칙으로도 성능이 개선되는 것을 보였다.

다수의 고장 원인을 갖는 기기의 신뢰성 모형화 및 분석 (Reliability Modeling and Analysis for a Unit with Multiple Causes of Failure)

  • 백상엽;임태진;이창훈
    • 대한산업공학회지
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    • 제21권4호
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    • pp.609-628
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    • 1995
  • This paper presents a reliability model and a data-analytic procedure for a repairable unit subject to failures due to multiple non-identifiable causes. We regard a failure cause as a state and assume the life distribution for each cause to be exponential. Then we represent the dependency among the causes by a Markov switching model(MSM) and estimate the transition probabilities and failure rates by maximum likelihood(ML) method. The failure data are incomplete due to masked causes of failures. We propose a specific version of EM(expectation and maximization) algorithm for finding maximum likelihood estimator(MLE) under this situation. We also develop statistical procedures for determining the number of significant states and for testing independency between state transitions. Our model requires only the successive failure times of a unit to perform the statistical analysis. It works well even when the causes of failures are fully masked, which overcomes the major deficiency of competing risk models. It does not require the assumption of stationarity or independency which is essential in mixture models. The stationary probabilities of states can be easily calculated from the transition probabilities estimated in our model, so it covers mixture models in general. The results of simulations show the consistency of estimation and accuracy gradually increasing according to the difference of failure rates and the frequency of transitions among the states.

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An Elliptical Basis Function Network for Classification of Remote-Sensing Images

  • Luo, Jian-Cheng;Chen, Qiu-Xiao;Zheng, Jiang;Leung, Yee;Ma, Jiang-Hong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1326-1328
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    • 2003
  • An elliptical basis function (EBF) network is proposed in this study for the classification of remotely sensed images. Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on mixture -density distributions in the feature space, the proposed network not only possesses the advantage of the RBF mechanism but also utilizes the EM algorithm to compute the maximum likelihood estimates of the mean vectors and covariance matrices of a Gaussian mixture distribution in the training phase. Experimental results show that the EM-based EBF network is faster in training, more accurate, and simpler in structure.

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Investigation of nuclear material using a compact modified uniformly redundant array gamma camera

  • Lee, Taewoong;Kwak, Sung-Woo;Lee, Wonho
    • Nuclear Engineering and Technology
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    • 제50권6호
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    • pp.923-928
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    • 2018
  • We developed a compact gamma camera based on a modified uniformly redundant array coded aperture to investigate the position of a $UO_2$ pellet emitting characteristic X-rays (98.4 keV) and ${\gamma}-rays$ (185.7 keV). Experiments using an only-mask method and an antimask subtractive method were conducted, and the maximum-likelihood expectation maximization algorithm was used for image reconstruction. The images obtained via the antimask subtractive method were compared with those obtained using the only-mask method with regard to the signal-to-noise ratio. The reconstructed images of the antimask subtractive method were superior. The reconstructed images of the characteristic X-rays and the ${\gamma}-rays$ were combined with the obtained image using the optical camera. The combined images showed the precise position of the $UO_2$ pellet. According to the self-absorption ratios of the nuclear material and the minimum number of effective events for image reconstruction, we estimated the minimum detection time depending on the amount of nuclear material.

지폐검사를 위한 UV 패턴의 자동추출 (Automatic Extraction of UV patterns for Paper Money Inspection)

  • 이건호;박태형
    • 한국지능시스템학회논문지
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    • 제21권3호
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    • pp.365-371
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    • 2011
  • 최근에 발행되는 대부분의 지폐는 UV(ultra violet)조명에 반응하는 UV패턴을 포함한다. 본 논문은 지폐검사를 위하여 지폐 내부에 존재하는 UV패턴을 자동으로 추출하는 방법을 제안한다. UV조명을 이용하여 촬영한 영상을 전 처리 과정을 통하여 입력데이터로 변환시킨 후, 가우시안 혼합 모형과 split-and merge EM(SMEM)알고리즘을 적용하여 영상을 몇 개의 영역으로 분리시킨다. 영역 분리된 영상 중 원하는 패턴을 추출하기 위하여, 공분산 벡터의 넓이와 가중치를 이용하는 방법을 새로이 제안한다. 다양한 지폐에 대한 실험을 통하여 제안방법의 유용성을 보인다.

누적 유사도 측정을 이용한 자동 임계값 결정 기법 - 다중분광 및 초분광영상의 무감독 변화탐지를 목적으로 (Automatic Thresholding Method using Cumulative Similarity Measurement for Unsupervised Change Detection of Multispectral and Hyperspectral Images)

  • 김대성;김형태
    • 대한원격탐사학회지
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    • 제24권4호
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    • pp.341-349
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    • 2008
  • 본 논문은 위성영상을 이용한 변화정보를 취득하는데 있어 중요한 과정인 임계값 결정에 관한 새로운 기법을 제안하고 있다. 화소간 유사도 측정을 통해 도출된 결과 값을 일정 간격으로 누적 계산하고, 급격하게 변하는 지점을 임계값으로 결정하였다. 의사영상을 통해 기대최대화 기법, 교점방법과 성능을 비교하였으며, 두 시기의 ALI 영상과 Hyperion 영상에 실제 적용하여 변화탐지 결과를 확인하였다. 제안된 기법은 기존의 기법과 비슷한 수준의 변화탐지 결과 정확도를 확보할 수 있었으며, 기대최대화 기법에 비해 간단하게 적용할 수 있고, 교점방법과 달리 최빈 값을 둘 이상 가지는 히스토그램에도 적용할 수 있는 장점이 있어 향후 변화유무 정보 취득에 효과적으로 사용할 수 있을 것으로 기대한다.

Maximum a posteriori estimation based wind fragility analysis with application to existing linear or hysteretic shear frames

  • Wang, Vincent Z.;Ginger, John D.
    • Structural Engineering and Mechanics
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    • 제50권5호
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    • pp.653-664
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    • 2014
  • Wind fragility analysis provides a quantitative instrument for delineating the safety performance of civil structures under hazardous wind loading conditions such as cyclones and tornados. It has attracted and would be expected to continue to attract intensive research spotlight particularly in the nowadays worldwide context of adapting to the changing climate. One of the challenges encumbering efficacious assessment of the safety performance of existing civil structures is the possible incompleteness of the structural appraisal data. Addressing the issue of the data missingness, the study presented in this paper forms a first attempt to investigate the feasibility of using the expectation-maximization (EM) algorithm and Bayesian techniques to predict the wind fragilities of existing civil structures. Numerical examples of typical linear or hysteretic shear frames are introduced with the wind loads derived from a widely used power spectral density function. Specifically, the application of the maximum a posteriori estimates of the distribution parameters for the story stiffness is examined, and a surrogate model is developed and applied to facilitate the nonlinear response computation when studying the fragilities of the hysteretic shear frame involved.