• 제목/요약/키워드: Weighting Scheme

검색결과 202건 처리시간 0.033초

CONVERGENCE OF MULTISPLITTING METHODS WITH DIFFERENT WEIGHTING SCHEMES

  • Oh, Se-Young;Yun, Jae-Heon;Han, Yu-Du
    • Journal of applied mathematics & informatics
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    • 제30권3_4호
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    • pp.593-602
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    • 2012
  • In this paper, we first introduce a special type of multisplitting method with different weighting scheme, and then we provide convergence results of multisplitting methods with different weighting schemes corresponding to both the AOR-like multisplitting and the SSOR-like multisplitting.

Extremely Low Numerical Dispersion FDTD Method Based on H(2, 4) Scheme for Lossy Material

  • Oh, Il-Young;Hong, Yongjun;Yook, Jong-Gwan
    • Journal of electromagnetic engineering and science
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    • 제13권3호
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    • pp.158-164
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    • 2013
  • This paper expands a previously proposed optimized higher order (2, 4) finite-difference time-domain scheme (H(2, 4) scheme) for use with lossy material. A low dispersion error is obtained by introducing a weighting factor and two scaling factors. The weighting factor creates isotropic dispersion, and the two scaling factors dramatically reduce the numerical dispersion error at an operating frequency. In addition, the results confirm that the proposed scheme performs better than the H(2, 4) scheme for wideband analysis. Lastly, the validity of the proposed scheme is verified by calculating a scattering problem of a lossy circular dielectric cylinder.

EXTENSION OF AUSMPW+ SCHEME FOR TWO-FLUID MODEL

  • Park, Jin Seok;Kim, Chongam
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제17권3호
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    • pp.209-219
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    • 2013
  • The present paper deals with the extension of AUSMPW+ scheme into two-fluid model for multiphase flow. AUSMPW+ scheme is the improvement of a single-phase AUSM+ scheme by designing pressure-based weighting functions to prevent oscillations near a wall and shock instability after a strong shock. Recently, Kitamura and Liou assessed a family of AUSM-type schemes with two-fluid model governing equations [K. Kitamura and M.-S. Liou, Comparative study of AUSM-Family schemes in compressible multi-phase flow simulations, ICCFD7-3702 (2012)]. It was observed that the direct application of the single-phase AUSMPW+ did not provide satisfactory results for most of numerical test cases, which motivates the current study. It turns out that, by designing pressure-based weighting functions, which play a key role in controlling numerical diffusion for two-fluid model, problems reported in can be overcome. Various numerical experiments validate the proposed modification of AUSMPW+ scheme is accurate and robust to solve multiphase flow within the framework of two-fluid model.

Inverted Pendulum 제어를 위한 새로운 하이브리드 퍼지게인스케쥴링 제어기의 설계

  • 정병태;박재삼
    • 한국산업정보학회:학술대회논문집
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    • 한국산업정보학회 1997년도 춘계학술대회 발표논문집
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    • pp.235-246
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    • 1997
  • Hybrid fuzzy gain scheduling controller is composed of a PD control and a fuzzy control for taking the advantage of each scheme. The key structure of the hybrid fuzzy gain scheduling control scheme is so called a switch which calculates weighting values between the fuzzy controller and the PD controller. However, due to the requirement of the switch , the hybrid fuzzy gain scheduling control scheme needs extra fuzzy logic processing, thus the structure is complicated. and requires more calculation time. To eliminate the drawbacks, a new hybrid fuzzy gain scheduling control scheme is proposed in this paper. In the proposed scheme, the membership function, for calculating of weithting value, and the input and output membership functions are combined. Thus the proposed hybrid scheme does not require switch for calculation of weighting value, and as a result, the calculation time is faster and the structure is more simple than the existing hybrid controller. Computer simulation results for an inverted pendulum model under Pole-Placement PID controller, fuzzy gain scheduling controller,existing hybrid controller , and proposed hybrid controller are compared to demonstrate the good property of the proposed hybrid controller.

Central Flux Scheme과 WENO Scheme을 이용한 고차 정확도 Hybrid Scheme의 개발 (Development of a High-Order Accurate Hybrid Scheme Using the Central Flux and WENO Schemes)

  • 권대희;권장혁
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2005년도 춘계 학술대회논문집
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    • pp.135-141
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    • 2005
  • A hybrid central-WENO scheme is proposed. The fifth order WENO-LF scheme is coupled with a central flux scheme at cell face. Two sub-schemes, the WENO-LF scheme and the central flux scheme, are switched by a weighting function. The efficiency and accuracy of the proposed hybrid central-WENO scheme is validated through several numerical experiments.

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Use of Word Clustering to Improve Emotion Recognition from Short Text

  • Yuan, Shuai;Huang, Huan;Wu, Linjing
    • Journal of Computing Science and Engineering
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    • 제10권4호
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    • pp.103-110
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    • 2016
  • Emotion recognition is an important component of affective computing, and is significant in the implementation of natural and friendly human-computer interaction. An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem. However, in emotion recognition, the texts involved are usually very short, leaving a very large, sparse feature space, which decreases the performance of emotion classification. This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster features, offering a novel word clustering algorithm, and using a new feature weighting scheme. Emotion classification experiments were performed with different features and weighting schemes on a publicly available dataset. The experimental results suggest that the word cluster features and the proposed weighting scheme can partly resolve problems with feature sparseness and emotion recognition performance.

Organ Shape Modeling Based on the Laplacian Deformation Framework for Surface-Based Morphometry Studies

  • Kim, Jae-Il;Park, Jin-Ah
    • Journal of Computing Science and Engineering
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    • 제6권3호
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    • pp.219-226
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    • 2012
  • Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.

프로세스의 독립성, 데이터 가중치 체계, 부분군 형성과 관리도 용도에 따른 합격판정 관리도의 설계 (Design of Acceptance Control Charts According to the Process Independence, Data Weighting Scheme, Subgrouping, and Use of Charts)

  • 최성운
    • 대한안전경영과학회지
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    • 제12권3호
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    • pp.257-262
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    • 2010
  • The study investigates the various Acceptance Control Charts (ACCs) based on the factors that include process independence, data weighting scheme, subgrouping, and use of control charts. USL - LSL > $6{\sigma}$ that used in the good condition processes in the ACCs are designed by considering user's perspective, producer's perspective and both perspectives. ACCs developed from the research is efficiently applied by using the simple control limit unified with APL (Acceptable Process Level), RLP (Rejectable Process Level), Type I Error $\alpha$, and Type II Error $\beta$. Sampling interval of subgroup examines i.i.d. (Identically and Independent Distributed) or auto-correlated processes. Three types of weight schemes according to the reliability of data include Shewhart, Moving Average(MA) and Exponentially Weighted Moving Average (EWMA) which are considered when designing ACCs. Two types of control charts by the purpose of improvement are also presented. Overall, $\alpha$, $\beta$ and APL for nonconforming proportion and RPL of claim proportion can be designed by practioners who emphasize productivity and claim defense cost.

마코브 연산 기반의 함정 분산 제어망을 위한 실시간 고장 노드 탐지 기법 연구 (Markov Model-Driven in Real-time Faulty Node Detection for Naval Distributed Control Networked Systems)

  • 노동희;김동성
    • 제어로봇시스템학회논문지
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    • 제20권11호
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    • pp.1131-1135
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    • 2014
  • This paper proposes the enhanced faulty node detection scheme with hybrid algorithm using Markov-chain model on BCH (Bose-Chaudhuri-Hocquenghem) code in naval distributed control networked systems. The probabilistic model-driven approach, on Markov-chain model, in this paper uses the faulty weighting interval factors, which are based on the BCH code. In this scheme, the master node examines each slave-nodes continuously using three defined states : Good, Warning, Bad-state. These states change using the probabilistic calculation method. This method can improve the performance of detecting the faulty state node more efficiently. Simulation results show that the proposed method can improve the accuracy in faulty node detection scheme for real-time naval distributed control networked systems.

뉴스 댓글의 감정 분류를 위한 자질 가중치 설정 (Feature Weighting for Opinion Classification of Comments on News Articles)

  • 이공주;김재훈;서형원;류길수
    • Journal of Advanced Marine Engineering and Technology
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    • 제34권6호
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    • pp.871-879
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    • 2010
  • 본 논문은 뉴스 기사의 댓글에 대한 사용자의 감정을 분류하는 시스템을 제안한다. 제안된 시스템은 댓글의 문서 분류 시스템으로 기계학습에 기반을 두고 있다. 댓글은 일반적인 문서와 달리 본문을 가지고 있으며 본문의 내용이 독자의 감정에 영향을 줄 수 있다. 본 논문에서는 이와 같은 댓글의 특성과 여러 가지 자원을 이용하여 감정 분류를 위한 자질을 제안하고 이들의 가중치 설정 방법을 제안한다. 실험을 통해 이러한 가중치 설정 방법이 한글 뉴스의 댓글에 대한 감정을 분류하는데 효과적임을 알 수 있었다. 또한 댓글과 같이 많은 오류를 포함하는 문서에 대해서 문자 단위의 2음절과 3음절 자질도 충분히 이용 가치가 있음을 확인할 수 있었다. 향후에 뉴스 기사의 댓글뿐 아니라 상품 댓글 등 일반적인 감정 분석에 적용할 계획이다.