• Title/Summary/Keyword: statistical shape model

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A Revised Fractal Technique With Fixed Midpoints For A Specific Terrain Model (고정 중간점을 허용하는 프랙탈 기법에 대한 연구)

  • No, Yong-Deok
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.1
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    • pp.160-166
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    • 1996
  • In 2D and 3D computer graphics, fractal techniques have been applied ter rain models. In general, a specific 3D terrain model such as Cheju or Uleung Island could not beformulated by statistical fractalsowing to the randomeffects. However, by locating the control points on the edges and the surface of a specific terrain such as Cheju Island, a similar shape of the terrain model can be simulated. This paper presents the way of formulating a specific 3D terrain model by the statistical fractals with fixed midpoints.

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Time-Varying Comovement of KOSPI 200 Sector Indices Returns

  • Kim, Woohwan
    • Communications for Statistical Applications and Methods
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    • v.21 no.4
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    • pp.335-347
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    • 2014
  • This paper employs dynamic conditional correlation (DCC) model to examine time-varying comovement in the Korean stock market with a focus on the financial industry. Analyzing the daily returns of KOSPI 200 eight sector indices from January 2008 to December 2013, we find that stock market correlations significantly increased during the GFC period. The Financial Sector had the highest correlation between the Constructions-Machinery Sector; however, the Consumer Discretionary and Consumer Staples sectors indicated a relatively lower correlation between the Financial Sector. In terms of model fitting, the DCC with t distribution model concludes as the best among the four alternatives based on BIC, and the estimated shape parameter of t distribution is less than 10, implicating a strong tail dependence between the sectors. We report little asymmetric effect in correlation dynamics between sectors; however, we find strong asymmetric effect in volatility dynamics for each sector return.

Application of Machine Learning to Predict Web-warping in Flexible Roll Forming Process (머신러닝을 활용한 가변 롤포밍 공정 web-warping 예측모델 개발)

  • Woo, Y.Y.;Moon, Y.H.
    • Transactions of Materials Processing
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    • v.29 no.5
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    • pp.282-289
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    • 2020
  • Flexible roll forming is an advanced sheet-metal-forming process that allows the production of parts with various cross-sections. During the flexible process, material is subjected to three-dimensional deformation such as transverse bending, inhomogeneous elongations, or contraction. Because of the effects of process variables on the quality of the roll-formed products, the approaches used to investigate the roll-forming process have been largely dependent on experience and trial- and-error methods. Web-warping is one of the major shape defects encountered in flexible roll forming. In this study, an SVR model was developed to predict the web-warping during the flexible roll forming process. In the development of the SVR model, three process parameters, namely the forming-roll speed condition, leveling-roll height, and bend angle were considered as the model inputs, and the web-warping height was used as the response variable for three blank shapes; rectangular, concave, and convex shape. MATLAB software was used to train the SVR model and optimize three hyperparameters (λ, ε, and γ). To evaluate the SVR model performance, the statistical analysis was carried out based on the three indicators: the root-mean-square error, mean absolute error, and relative root-mean-square error.

STATISTICAL PROPERTIES OF GRAVITATIONAL LENSING IN COSMOLOGICAL MODELS WITH COSMOLOGICAL CONSTANT

  • LEE HYUN-A;PARK MYEONG-GU
    • Journal of The Korean Astronomical Society
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    • v.27 no.2
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    • pp.103-117
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    • 1994
  • To extend the work of Gott, Park, and Lee (1989), statistical properties of gravitational lensing in a wide variety of cosmological models involving non-zero cosmological constant is investigated, using the redshifts of both lens and source and observed angular separation of images for gravitational lens systems. We assume singular isothermal sphere as lensing galaxy in homogenous and isotropic Friedmann­Lemaitre-Robertson- Walker universe, Schechter luminosity function, standard angular diameter distance formula and other galaxy parameters used in Fukugita and Turner (1991). To find the most adequate flat cosmological model and put a limit on the value of dimensionless cosmological constant $\lambda_0$, the mean value of the angular separation of images, probability distribution of angular separation and cumulative probability are calculated for given source and lens redshifts and compared with the observed values through several statistical methods. When there is no angular selection effect, models with highest value of $\lambda_0$ is preferred generally. When the angular selection effects are considered, the preferred model depends on the shape of the selection functions and statistical methods; yet, models with large $\lambda_0$ are preferred in general. However, the present data can not rule out any of the flat universe models with enough confidence. This approach can potentially select out best model. But at the moment, we need more data.

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Statistical Space-Time Metamodels Based on Multiple Responses Approach for Time-Variant Dynamic Response of Structures (구조물의 시간-변화 동적응답에 대한 다중응답접근법 기반 통계적 공간-시간 메타모델)

  • Lee, Jin-Min;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.8
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    • pp.989-996
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    • 2010
  • Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

A Note on Sudden Death Tests (sudden death 시험에 대한 고찰)

  • Seo, Sun-Keun
    • Journal of Applied Reliability
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    • v.12 no.3
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    • pp.139-152
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    • 2012
  • Successive and simultaneous sudden death tests are compared with the complete and Type II censored samples in terms of expected test duration and Total Time on Test(TTT) subject to the same number of failures in order to maintain the equal statistical precision under Weibull lifetime distribution with known shape parameter. Also, two sudden death tests under a proposed cost model are discussed and a numerical example is provided to illustrate the use of the proposed cost model.

Bayesian Method on Sequential Preventive Maintenance Problem

  • Kim Hee-Soo;Kwon Young-Sub;Park Dong-Ho
    • Communications for Statistical Applications and Methods
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    • v.13 no.1
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    • pp.191-204
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    • 2006
  • This paper develops a Bayesian method to derive the optimal sequential preventive maintenance(PM) policy by determining the PM schedules which minimize the mean cost rate. Such PM schedules are derived based on a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) and may have unequal length of PM intervals. To apply the Bayesian approach in this problem, we assume that the failure times follow a Weibull distribution and consider some appropriate prior distributions for the scale and shape parameters of the Weibull model. The solution is proved to be finite and unique under some mild conditions. Numerical examples for the proposed optimal sequential PM policy are presented for illustrative purposes.

A Study on the Compressive Capacity of Yellow Poplar Skin-timber (백합나무 스킨팀버의 압축 성능에 관한 연구)

  • Kim, Gwang-Chul
    • Journal of the Korean Wood Science and Technology
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    • v.39 no.4
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    • pp.333-343
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    • 2011
  • The yellow poplar is an appropriate species for the age of low carbon green growth, because its absorption rates of ozone is greatly excellent, and also the absorption rates of carbon dioxide causing climate changes is very remarkable. The yellow poplar, which is a kind of rapid growth tree, shows a lack of performance as a structural member, however, it is suitable to use a variety of purposes like furniture materials, interior materials, plywood materials, and so on. In this study, the structural size skin-timbers were made by using the yellow poplar, and the compressive capacity was evaluated, also the numerical model was developed for the various uses. The rectangular shape skin-timber presented a good performance by showing 56.3% residual strength about the solid material. In case of the cylinder shape skin-timber showed a possibility to use diversely as a furniture material, as well as a structural uses, because almost 50% compressive capacity of material even though its residual area rates was 25%. Both rectangular shape and the cylinder shape represented that 'Brooming or end rolling' were the major failure mode, and partly splitting failure mode. The compressive capacity of the rectangular shape which residual area rates was large was higher than the cylinder shape, but it did not show statistical significance about the compressive capacity between them. Thus, it will be possible to use them mixed for a convenience of users. The result of the numerical analysis model was quite similar to actual test of the compressive capacity. Therefore, the yellow poplar can be utilized in the development of various uses by applying numerical analysis model about a variety of shapes and dimensions.

Development of 3D statistical mandible models for cephalometric measurements

  • Kim, Sung-Goo;Yi, Won-Jin;Hwang, Soon-Jung;Choi, Soon-Chul;Lee, Sam-Sun;Heo, Min-Suk;Huh, Kyung-Hoe;Kim, Tae-Il;Hong, Helen;Yoo, Ji-Hyun
    • Imaging Science in Dentistry
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    • v.42 no.3
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    • pp.175-182
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    • 2012
  • Purpose: The aim of this study was to provide sex-matched three-dimensional (3D) statistical shape models of the mandible, which would provide cephalometric parameters for 3D treatment planning and cephalometric measurements in orthognathic surgery. Materials and Methods: The subjects used to create the 3D shape models of the mandible included 23 males and 23 females. The mandibles were segmented semi-automatically from 3D facial CT images. Each individual mandible shape was reconstructed as a 3D surface model, which was parameterized to establish correspondence between different individual surfaces. The principal component analysis (PCA) applied to all mandible shapes produced a mean model and characteristic models of variation. The cephalometric parameters were measured directly from the mean models to evaluate the 3D shape models. The means of the measured parameters were compared with those from other conventional studies. The male and female 3D statistical mean models were developed from 23 individual mandibles, respectively. Results: The male and female characteristic shapes of variation produced by PCA showed a large variability included in the individual mandibles. The cephalometric measurements from the developed models were very close to those from some conventional studies. Conclusion: We described the construction of 3D mandibular shape models and presented the application of the 3D mandibular template in cephalometric measurements. Optimal reference models determined from variations produced by PCA could be used for craniofacial patients with various types of skeletal shape.

Texture analysis of Thyroid Nodules in Ultrasound Image for Computer Aided Diagnostic system (컴퓨터 보조진단을 위한 초음파 영상에서 갑상선 결절의 텍스쳐 분석)

  • Park, Byung eun;Jang, Won Seuk;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.20 no.1
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    • pp.43-50
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    • 2017
  • According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.