• Title/Summary/Keyword: Weighted combination

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Adaptive Finite Element Analysis of an Enclosed Die Forging Process of a Bevel Gear and its Experimental Verification (베벨기어 폐쇄냉간단조 공정의 지능형 유한요소해석과 결과의 검증)

  • Lee Min-Cheal;Park Rae-Hun;Jun Byoung-Yoon;Joun Man-Soo
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.4 s.181
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    • pp.37-43
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    • 2006
  • In this paper, an approach to adaptive finite element analysis of three-dimensional forging processes is presented with emphasis on remeshing. In the approach, an optimal tetrahedral element generation technique is employed and the mesh density is specified by the combination of the weighted normalized effective strain and the normalized effective strain rate as well as the weighted normalized curvature. The approach is applied to computer simulation of an enclosed die forging process of a bevel gear and its results are compared with its related experiments. It has been shown that the analyzed results are in good agreement with the experimental ones.

A Combination and Calibration of Multi-Model Ensemble of PyeongChang Area Using Ensemble Model Output Statistics (Ensemble Model Output Statistics를 이용한 평창지역 다중 모델 앙상블 결합 및 보정)

  • Hwang, Yuseon;Kim, Chansoo
    • Atmosphere
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    • v.28 no.3
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    • pp.247-261
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    • 2018
  • The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

Approximated Posterior Probability for Scoring Speech Recognition Confidence

  • Kim Kyuhong;Kim Hoirin
    • MALSORI
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    • no.52
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    • pp.101-110
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    • 2004
  • This paper proposes a new confidence measure for utterance verification with posterior probability approximation. The proposed method approximates probabilistic likelihoods by using Viterbi search characteristics and a clustered phoneme confusion matrix. Our measure consists of the weighted linear combination of acoustic and phonetic confidence scores. The proposed algorithm shows better performance even with the reduced computational complexity than those utilizing conventional confidence measures.

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Modified Raised-Cosine Interpolation and Application to Image Processing (변형된 상승여현 보간법의 제안과 영상처리에의 응용)

  • 하영호;김원호;김수중
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.4
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    • pp.453-459
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    • 1988
  • A new interpolation function, named modified raised-cosine interpolation, is proposed. This function is derived from the linear combination of weighted triangular and raised-cosine functions to reduce the effect of side lobes which incur the interpolation error. Interpolation error reduces significantly for higher-order convolutional interpolation functions of linear operators, but at the expense of resolution error due to the attenuation of main lobe. However, the proposed interpolation function enables us to reduce the side lobes as well as to preserve the main lobe. To prove practicality, this function is applied in image reconstruction and enlargement.

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Utterance Verification Using Anti-models Based on Neighborhood Information (이웃 정보에 기초한 반모델을 이용한 발화 검증)

  • Yun, Young-Sun
    • MALSORI
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    • no.67
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    • pp.79-102
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    • 2008
  • In this paper, we investigate the relation between Bayes factor and likelihood ratio test (LRT) approaches and apply the neighborhood information of Bayes factor to building an alternate hypothesis model of the LRT system. To consider the neighborhood approaches, we contemplate a distance measure between models and algorithms to be applied. We also evaluate several methods to improve performance of utterance verification using neighborhood information. Among these methods, the system which adopts anti-models built by collecting mixtures of neighborhood models obtains maximum error rate reduction of 17% compared to the baseline, linear and weighted combination of neighborhood models.

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Speech Recognition in the Noisy Environment using Weighted Projection-Based Likelihood Measure and Parallel Model Combination (가중 투영 우도 측정 및 병렬 모델 결합을 이용한 잡음 환경에서의 음성 인식)

  • 신원호;양태영;김원구;윤대희;차일환
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.1
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    • pp.49-54
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    • 1998
  • 본 논문에서는 잡음이 존재하는 환경에 강인한 것으로 알려져 있는 투영 방법을 우 도 측정에 가중 함수와 결합하여 사용하는 방법을 제안하였다. 반연속 HMM을 이용한 고립 단어의 인식 실험 결과, 제안한 방법이 실험에 사용된 잡음의 환경들에서 모두 좋은 성능을 나타내었다. 아울러 병렬 모델 결합 방법을 반연속 HMM에 적용하였는데 이는 코드북의 변 환반으로 쉽게 잡음의 특성을 반영할 수 있다. 가중 투영 우도 측정 방법을 병렬 모델 결합 방법에 적용한 경우에도 우수한 성능을 거둘 수 있었다.

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A New Input Estimation Algorithm for Target Tracking Problem

  • Lee, Hungu;Tahk, Min-Jea
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.323-328
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    • 1998
  • In this paper, a new input estimation algorithm is proposed for target tracking problem. The unknown target maneuver is approximated by a linear combination of independent time functions and the coefficients are estimated by using a weighted least-squares estimation technique. The proposed algorithm is verified by computer simulation of a realistic two-dimensional tracking problem. The proposed algorithm provides significant improvements in estimation performance over the conventional input estimation techniques based on the constant-input assumption.

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Stereo Matching Using Independent Component Analysis

  • Jeon, S.H.;Lee, K.H.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.496-498
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    • 2003
  • Signal is composed of the independent components that can describe itself. These components can distinguish itself from any other signals and be extracted by analysis itself. This algorithm is called Independent Component Analysis (ICA) and image signal is considered as linear combination of independent components and features that is the weighted vector of independent component. This algorithm is already used in order to extract the good feature for image classification and very effective In this paper, we'll explain the method of stereo matching using independent component analysis and show the experimental result.

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SOME PROPERTIES OF TOEPLITZ OPERATORS WITH SYMBOL μ

  • Kang, Si Ho
    • Journal of the Chungcheong Mathematical Society
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    • v.23 no.3
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    • pp.471-479
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    • 2010
  • For a complex regular Borel measure ${\mu}$ on ${\Omega}$ which is a subset of ${\mathbb{C}}^k$, where k is a positive integer we define the Toeplitz operator $T_{\mu}$ on a reproducing analytic space which comtains polynomials. Using every symmetric polynomial is a polynomial of elementary polynomials, we show that if $T_{\mu}$ has finite rank then ${\mu}$ is a finite linear combination of point masses.

The Clustering of Parts with Qualitative and Quantitative Quality Properties using λ-Fuzzy Measure (λ-퍼지측도를 사용한 질적, 양적혼합품질특성을 가진 부품의 군집화)

  • Kim, Jeong-Man;Lee, Sang-Do
    • Journal of Korean Society for Quality Management
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    • v.24 no.1
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    • pp.126-136
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    • 1996
  • In multi-item production system, GT(Group Technology) is used effectively in order to cluster various parts into groups. GT is based on clustering parts which have similar features, and these features are classified into two properties, namely crisp(quantitative) feature and fuzzy(qualitative) feature. Especially, many difficult problems are often faced that have to evaluate the properties of parts with the crisp and fuzzy feature together. As the basis of determining the similarity of inter-parts, in this method, one aggregate value is calculated on each part. However, because the above aggregate value is only gained from simple additive weighted sum, there is one problem in this method that has been handled the combination effect of inter-parts. For these reasons, in this paper, a proposed method is suggested for representing combination effect in order to cluster parts that have crisp and fuzzy properties into groups using ${\lambda}$-fuzzy measure and fuzzy integral.

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