• 제목/요약/키워드: Smoothing function

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SMOOTHING METHOD OF AUTO-BODY PART CONTOUR FOR THE DIE-FACE DESIGN SYSTEM BASED ON THE CAE PLATFORM

  • Gong, K.J.;Guo, W.;Hu, P.
    • International Journal of Automotive Technology
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    • 제7권7호
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    • pp.853-858
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    • 2006
  • The method of die-face design based on the CAE platform for automobile panels can fast modify the die addendum. In contrast with the process of the die-face design based on the CAD platform, there are some special steps for the die-face design based on the CAE platform. The most obvious difference is that the auto-body part contour needs smoothing arlier than the design of addendum surfaces does. It is helpful to improve the design quality of addendum surface. In spite of extensive researches on the smoothing technique, here is still dearth of the published solutions about smoothing the part contour with additional surface. This paper attempts to analyze the difficulties and provides practical solutions. Main results include the algorithm to calculate the segments needing to be smoothed on boundary, the strategy to create the smoothing curve and the procedure of surface generation. The relevant function modules for parametric design are developed. A few examples and suggestions for future work conclude the paper.

어레이 설계 응용을 위한 랜덤어레이의 통계적 성질 (Statistical Properties of Random Sparse Arrays with Application to Array Design)

  • Kook, Hyung-Seok;Davies, Patricia;Bolton, J.Stuart
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2000년도 춘계학술대회논문집
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    • pp.1493-1510
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    • 2000
  • Theoretical models that can be used to predict the range of main lobe widths and the probability distribution of the peak sidelobe levels of two-dimensionally sparse arrays are presented here. The arrays are considered to comprise microphones that are randomly positioned on a segmented grid of a given size. First, approximate expressions for the expected squared magnitude of the aperture smoothing function and the variance of the squared magnitude of the aperture smoothing function about this mean are formulated for the random arrays considered in the present study. By using the variance function, the mean value and the lower end of the range i.e., the first I percent of the mainlobe distribution can be predicted with reasonable accuracy. To predict the probability distribution of the peak sidelobe levels, distributions of levels are modeled by a Weibull distribution at each peak in the sidelobe region of the expected squared magnitude of the aperture smoothing function. The two parameters of the Weibull distribution are estimated from the means and variances of the levels at the corresponding locations. Next, the probability distribution of the peak sidelobe levels are assumed to be determined by a procedure in which the peak sidelobe level is determined as the maximum among a finite number of independent random sidelobe levels. It is found that the model obtained from the above approach predicts the probability density function of the peak sidelobe level distribution reasonably well for the various combinations of two different numbers of microphones and grid sizes tested in the present study. The application of these models to the design of random, sparse arrays having specified performance levels is also discussed.

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Robust Cross Validation Score

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.413-423
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    • 2005
  • Consider the problem of estimating the underlying regression function from a set of noisy data which is contaminated by a long tailed error distribution. There exist several robust smoothing techniques and these are turned out to be very useful to reduce the influence of outlying observations. However, no matter what kind of robust smoother we use, we should choose the smoothing parameter and relatively less attention has been made for the robust bandwidth selection method. In this paper, we adopt the idea of robust location parameter estimation technique and propose the robust cross validation score functions.

Comparison of Jump-Preserving Smoothing and Smoothing Based on Jump Detector

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • 제16권3호
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    • pp.519-528
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    • 2009
  • This paper deals with nonparametric estimation of discontinuous regression curve. Quite number of researches about this topic have been done. These researches are classified into two categories, the indirect approach and direct approach. The major goal of the indirect approach is to obtain good estimates of jump locations, whereas the major goal of the direct approach is to obtain overall good estimate of the regression curve. Thus it seems that two approaches are quite different in nature, so people say that the comparison of two approaches does not make much sense. Therefore, a thorough comparison of them is lacking. However, even though the main issue of the indirect approach is the estimation of jump locations, it is too obvious that we have an estimate of regression curve as the subsidiary result. The point is whether the subsidiary result of the indirect approach is as good as the main result of the direct approach. The performance of two approaches is compared through a simulation study and it turns out that the indirect approach is a very competitive tool for estimating discontinuous regression curve itself.

SPECKLE NOISE SMOOTHING USING AN MODIFIED MEAN CURVATURE DIFFUSION FILTER

  • Ye, Chul-Soo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.159-162
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    • 2008
  • This paper presents a modified mean curvature diffusion filter to smooth speckle noise in images. Mean curvature diffusion filter has already shown good results in reducing noise in images while preserving fine details. In the mean curvature diffusion, the rate of smoothing is controlled by the local value of the diffusion coefficient chosen to be a function of the local image gradient magnitude. In this paper, the diffusion coefficient is modified to be controlled adaptively by local image surface slope and heterogeneity. The local surface slope contributes to preserving details (e.g.edges) in image and the local surface heterogeneity helps the smoothing filter consider the amount of noise in both edge and non-edge area. The proposed filter's performance is demonstrated by quantitative experiments using speckle noised aerial image and TerraSAR-X satellite image.

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Negative Binomial Varying Coefficient Partially Linear Models

  • Kim, Young-Ju
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.809-817
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    • 2012
  • We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.

라벨 스무딩을 활용한 치은염 이진 분류기 캘리브레이션 (Calibration for Gingivitis Binary Classifier via Epoch-wise Decaying Label-Smoothing)

  • 이상현
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 추계학술대회
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    • pp.594-596
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    • 2021
  • Future healthcare systems will heavily rely on ill-labeled data due to scarcity of the experts who are trained enough to label the data. Considering the contamination of the dataset, it is not desirable to make the neural network being overconfident to the dataset, but rather giving them some margins for the prediction is preferable. In this paper, we propose a novel epoch-wise decaying label-smoothing function to alleviate the model over-confidency, and it outperforms the neural network trained with conventional cross entropy by 6.0%.

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급격한 조명 변화에 강건한 동영상 대조비 개선 방법 (Robust Method of Video Contrast Enhancement for Sudden Illumination Changes)

  • 박진욱;문영식
    • 전자공학회논문지
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    • 제52권11호
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    • pp.55-65
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    • 2015
  • 동영상 대조비 개선 과정에서 단일 영상을 위해 연구된 대조비 개선 방법들을 사용할 수 있지만, 동영상의 연속성이 고려되지 않으면 원본 동영상에 없는 깜박임을 야기할 수 있다. 또한 동영상의 연속성을 고려하는 경우, 깜박임은 억제할 수 있지만 연속성 때문에 조명의 급격한 변화할 때 불필요한 페이드인/아웃(fade-in/out) 현상이 발생하는 단점이 발생할 수 있다. 본 논문에서는 깜박임과 페이드인/아웃 현상 없이 동영상의 대조비를 개선하는 방법을 제안한다. 제안하는 방법은 Fast Gray-Level Grouping(FGLG)를 사용하여 각 프레임의 대조비를 개선하고, 깜박임을 억제하기 위해 Exponential smoothing 필터를 사용한다. 불필요한 페이드인/아웃 현상을 억제하기 위해서는 S형 함수로 Exponential smoothing 필터의 평활화 비율을 프레임 별로 적응적으로 계산하여 적용한다. 실험에서 제안하는 방법과 기존의 방법들은 6가지 측정 기준을 적용하여 성능을 비교 및 분석한다. 실험 결과, 제안하는 방법은 영상 형태 보존을 측정하는 MSSIM과 깜박임을 측정하는 Flickering score에서 정량적으로 가장 높은 결과를 보여주었으며, 시각적인 품질 비교를 통해 조명 변화에 따른 적응적인 개선을 정성적 결과로 입증하였다.

능동형 RFID 리더를 위한 효율적인 리더 프로토콜의 구현 (Implementation of An Efficient Reader Protocol for Active RFID Readers)

  • 문영식;정상화
    • 한국통신학회논문지
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    • 제34권8B호
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    • pp.822-829
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    • 2009
  • 리더 프로토콜은 RFID 리더와 호스트 사이의 명령 수행/응답 및 태그 정보 교환을 담당하는 인터페이스이며, 관련된 표준들로 EPCglobal Low Level Reader Protocol(LLRP) 1.0.1, EPCglobal Reader Protocol(RP) 1.1 그리고 ISO/IEC 15961,15962 등이 있다. 하지만 현재 리더 프로토콜 표준들은 수동형 RFID 시스템에 초점을 두고 있어 능동형 RFID 시스템에서는 효율적이지 못하다. 본 논문에서는 EPCglobal LLRP 1.0.1을 기본으로 EPCglobal RP 1.1의 smoothing/filtering 기능을 추가하여 능동형 RFID 시스템에 효율적인 리더 프로토콜을 구현하였다. 구현한 리더 프로토콜은 RF 트랜시버와 RFID 리더와 태그 간의 Air interface 파라미터를 직접 설정 할 수 있다. 그리고 filtering 기능을 이용 리더와 호스트 간의 데이터 전송량을 줄이고, smoothing 기능을 이용 태그 수집 시 태그 수집성능 향상을 기대할 수 있으며, ISO/IEC 15961,15962 표준에 따른 태그 메모리 데이터 변경시 발생하는 비효율성을 제거 하였다. 또한, 하나의 리더와 45개의 태그를 사용하여 구현한 리더 프로토콜을 실제 능동형 RFID 시스템에 적용하여 성능을 평가 하였다.

A Study on Properties of the survival function Estimators with Weibull approximation

  • Lee, Jae-Man;Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • 제14권2호
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    • pp.279-287
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    • 2003
  • In this paper we propose a local smoothing of the Nelson type estimator for the survival function based on an approximation by the Weibull distribution function. It appears that Mean Square Error and Bias of the smoothed estimator of the Nelson type survival function estimators are significantly smaller than that of the smoothed estimator of the Kaplan-Meier survival function estimator.

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