• Title/Summary/Keyword: hierarchical estimation

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Adaptive Finite Element Analysis of 2-D Plane Problems Using the R-P version (R-P법에 의한 이차원 평면문제의 적응 유한요소 해석)

  • Chung, Sang-Wook;Lim, Jang-Keun
    • Proceedings of the KSME Conference
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    • 2000.04a
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    • pp.345-350
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    • 2000
  • Adaptive finite element analysis, which its solution error meets with the user defined allowable error, is recently used far improving reliability of finite element analysis results. This adaptive analysis is composed of two procedures; one is the error estimation of an analysis result and another is the reconstruction of finite elements. In the rp-method, an element size is controlled by relocating of nodal positions(r-method) and the order of an element shape function is determined by the hierarchical polynomial(p-method) corresponding to the element solution error. In order to show the effectiveness and accuracy of the suggested rp-method, various numerical examples were analyzed and these analysis results were examined by comparing with those obtained by the existed methods. As a result of this study, following conclusions are obtained. (1) rp-method is more accurate and effective than the r- and p-method. (2) The solution convergency of the rp-method is controlled by means of the iterative calculation numbers of the r- and p- method each other.

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Velocity Dispersion Bias of Galaxy Groups classified by Machine Learning Algorithm

  • Lee, Youngdae;Jeong, Hyunjin;Ko, Jongwan;Lee, Joon Hyeop;Lee, Jong Chul;Lee, Hye-Ran;Yang, Yujin;Rey, Soo-Chang
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.74.2-74.2
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    • 2019
  • We present a possible bias in the estimation of velocity dispersions for galaxy groups due to the contribution of subgroups which are infalling into the groups. We execute a systematic search for flux-limited galaxy groups and subgroups based on the spectroscopic galaxies with r < 17.77 mag of SDSS data release 12, by using DBSCAN (Density-Based Spatial Clustering of Application with Noise) and Hierarchical Clustering Method which are well known unsupervised machine learning algorithm. A total of 2042 groups with at least 10 members are found and ~20% of groups have subgroups. We found that the estimation of velocity dispersions of groups using total galaxies including those in subgroups are underestimated by ~10% compared to the case of using only galaxies in main groups. This result suggests that the subgroups should be properly considered for mass measurement of galaxy groups based on the velocity dispersion.

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An Effective Early Termination Motion Estimation Method for Multi-view Video Coding (다시점 비디오 부호화를 위한 효과적인 초기 종료 움직임 추정 기법)

  • Yoon, Hyo-Sun;Kim, Mi-Young
    • Journal of Korea Multimedia Society
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    • v.17 no.3
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    • pp.333-341
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    • 2014
  • Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. Multi-view video coding requires high computational complexity. To reduce computational complexity and maintain the image quality, an effective early termination motion estimation method is proposed in this paper. The proposed method exploiting the characteristic of motion vector distribution uses a hierarchical search strategy. This strategy method consists of multi-grid square search pattern, modified diamond search pattern, small diamond search pattern and raster search pattern. Experiment results show that the speedup improvement of the proposed method over TZ search method and FS(Full Search) method JMVC (Joint Multiview Video Coding) can be up to 1.7~4.5 times and 90 times faster respectively while maintaining similar video quality and bit rates.

Korean Welfare Panel Data: A Computational Bayesian Method for Ordered Probit Random Effects Models

  • Lee, Hyejin;Kyung, Minjung
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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    • pp.45-60
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    • 2014
  • We introduce a MCMC sampling for a generalized linear normal random effects model with the ordered probit link function based on latent variables from suitable truncated normal distribution. Such models have proven useful in practice and we have observed numerically reasonable results in the estimation of fixed effects when the random effect term is provided. Applications that utilize Korean Welfare Panel Study data can be difficult to model; subsequently, we find that an ordered probit model with the random effects leads to an improved analyses with more accurate and precise inferences.

A PHOTOMETRIC STUDY ON THE FORMATION OF THE EARLY TYPE GALAXIES IN NEARBY GALAXY CLUSTERS

  • KIM TAEHYUN;LEE MYUNG GYOON
    • Journal of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.145-148
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    • 2005
  • We present a photometric study of galaxies in the central regions of six nearby galaxy clusters at redshift z=0.0231${\~}$0.0951. We have derived BVI photometry of the galaxies from the CCD images obtained at the Bohyunsan Optical Astronomical Observatory (BOAO) in Korea, and JHKs photometry of the bright galaxies from the 2MASS extended source catalog. Comparing the galaxy photometry results with the simple stellar population model of Bruzual & Charlot (2003) in the optical & NIR color-color diagrams, we have estimated the ages and metallicities of early type galaxies. We have found that the observed galaxies had recent star-formation mostly 5 ${\~}$ 7 Gyrs ago but the spread in age estimation is rather large. The average metallicities are [Fe/H]=0.l${\~}$0.5 dex. These results support the hypothesis that large early type galaxies in clusters are formed via hierarchical merging of smaller galaxies.

Bayesian Methods for Wavelet Series in Single-Index Models

  • Park, Chun-Gun;Vannucci, Marina;Hart, Jeffrey D.
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.83-126
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    • 2005
  • Single-index models have found applications in econometrics and biometrics, where multidimensional regression models are often encountered. Here we propose a nonparametric estimation approach that combines wavelet methods for non-equispaced designs with Bayesian models. We consider a wavelet series expansion of the unknown regression function and set prior distributions for the wavelet coefficients and the other model parameters. To ensure model identifiability, the direction parameter is represented via its polar coordinates. We employ ad hoc hierarchical mixture priors that perform shrinkage on wavelet coefficients and use Markov chain Monte Carlo methods for a posteriori inference. We investigate an independence-type Metropolis-Hastings algorithm to produce samples for the direction parameter. Our method leads to simultaneous estimates of the link function and of the index parameters. We present results on both simulated and real data, where we look at comparisons with other methods.

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Hierarchical Multidirectional Motion Estimation Algorithm for Frame Rate Up-Conversion (프레임 율 향상을 위한 계층적 다방향 움직임 추정 알고리즘)

  • Yu, Songhyun;Park, Bumjun;Jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2017.06a
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    • pp.70-73
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    • 2017
  • 본 논문에서 프레임 율 향상을 위한 새로운 움직임 추정 알고리즘에 대해 제안한다. 계산량을 줄이고 다해상도의 영상을 이용하기 위하여 원본 프레임들을 계층적 구조로 형성하고, 최상위 계층에서 단방향 움직임 추정을 수행한다. 최상위 계층은 낮은 해상도 때문에 움직임 벡터의 정확도가 낮아지므로, 정확도를 향상시키기 위해 각각의 블록은 5 개의 움직임 벡터 후보들을 가진다. 이 후보들은 아래 계층들에서 수정되며, 움직임 추정이 완료되면 최하위 계층의 움직임 벡터들은 SAD (sum of absolute difference) 값을 이용해서 최종적으로 수정된다. 이렇게 구해진 단방향 움직임 벡터들은 양방향 움직임 벡터로 변환되고 양방향 보간법을 사용하여 보간 프레임을 생성한다. 결과적으로, 제안하는 알고리즘은 기존 알고리즘들에 비해 낮은 계산량을 나타내면서 PSNR (peak signal-to-noise ratio) 수치에서 최대 1.3 dB 의 향상을 나타냈고, 주관적으로도 더 선명한 결과를 보여주었다.

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Exploratory Methods for Joint Distribution Valued Data and Their Application

  • Igarashi, Kazuto;Minami, Hiroyuki;Mizuta, Masahiro
    • Communications for Statistical Applications and Methods
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    • v.22 no.3
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    • pp.265-276
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    • 2015
  • In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

Operation-level Early Termination Algorithm for Inter-predictions in HEVC

  • Rhee, Chae Eun
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.4
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    • pp.235-242
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    • 2016
  • The emerging High-Efficiency Video Coding (HEVC) standard attempts to improve coding efficiency by a factor of two over H.264/Advanced Video Coding (AVC) at the expense of an increase in computational complexity. Mode decision with motion estimation (ME) is still one of the most time-consuming computations in HEVC, as it is with H.264/AVC. Thus, fast mode decisions are not only an important issue to be researched, but also an urgent one. Several schemes for fast mode decisions have been presented in reference software and in other studies. However, the conventional hierarchical mode decision can be useless when block-level parallelism is exploited. This paper proposes operation-level exploration that offers more chances for early termination. An early termination condition is checked between integer and fractional MEs and between the parts of one partition type. The fast decision points of the proposed algorithm do not overlap those in previous works. Thus, the proposed algorithms are easily used with other fast algorithms, and consequently, independent speed-up is possible.

Path Planning for Static Obstacle Avoidance: ADAM III (정적 장애물 회피를 위한 경로 계획: ADAM III)

  • Choi, Heejae;Song, Bongsob
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.3
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    • pp.241-249
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    • 2014
  • This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.