• 제목/요약/키워드: Parametric information

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피처 트리와 매크로 파일을 이용하는 하이브리드 파라메트릭 번역기 (A Hybrid Parametric Translator Using the Feature Tree and the Macro File)

  • 문두환;김병철;한순흥
    • 한국CDE학회논문집
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    • 제7권4호
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    • pp.240-247
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    • 2002
  • Most commercial CAD systems provide parametric modeling functions, and by using these capabilities designers can edit a CAD model in order to create design variants. It is necessary to transfer parametric information during a CAD model exchange to modify the model inside the receiving system. However, it is not possible to exchange parametric information of CAD models based on the cur-rent version of STEP. The designer intents which are contained in the parametric information can be lost during the STEP transfer of CAD models. This paper introduces a hybrid CAB model translator, which also uses the feature tree of commercial CAD systems in addition to the macro file to allow transfer of parametric information. The macro-parametric approach is to exchange CAD models by using the macro file, which contains the history of user commands. To exchange CAD models using the macro-parametric approach, the modeling commands of several commercial CAD systems are analyzed. Those commands are classified and a set of standard modeling commands has been defined. As a neutral fie format, a set of standard modeling commands has been defined. Mapping relations between the standard modeling commands set and the native modeling commands set of commercial CAD systems are defined. The scope of the current version is limited to parts modeling and assemblies are excluded.

매크로 파라메트릭 방법론은 이용한 CAD 모델의 교환 (Exchange of CAD Models Using Macro Parametric Approach)

  • 문두환;한순흥
    • 한국CDE학회논문집
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    • 제6권4호
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    • pp.254-262
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    • 2001
  • It is not possible to exchange parametric information of CAD (Computer Aided Design) models based on the current version of STEP (Standard leer the Exchange of Product model data). The design intent can be lost during the STEP transfer of CAD models. The ISO Parametrics Group has proposed the SMCH (Solid Model Construction History) schema in June 2000 that includes structures fur exchange of parametric information. This paper proposes the macro parametric approach that is intended to provide capabilities to transfer parametric information. In this approach, CAD models are exchanged in the form of macro files. The macro file contains user commands which are used in the modeling phase. To exchange CAD models using the macro parametric approach, modeling commands of commercial CAD systems are analyzed. Those commands are classified by the grouping method suggested by Bill Anderson. As a neutral file format, a standard modeling commands set has been defined. Mapping relations between the standard modeling commands set and the native modeling commands set of commercial CAD systems are defined.

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Exchange of CAD Part Models Based on the Macro-Parametric Approach

  • Choi, Guk-Heon;Mun, Du-Hwan;Han, Soon-Hung
    • International Journal of CAD/CAM
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    • 제2권1호
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    • pp.13-21
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    • 2002
  • It is not possible to exchange parametric information of CAD models based on the current version of STEP. The design intent can be lost during the STEP transfer of CAD models. The Parametrics Group of ISO/TC184/SC4 has proposed the SMCH schema, which includes constructs for exchange of parametric information. This paper proposes a macro-parametric approach that is intended to provide capabilities to transfer parametric information including design intents. In this approach, CAD models are exchanged in the form of macro files. The macro file contains the history of user commands, which are used in the modeling phase. To exchange CAD models using the macro-parametric approach, the modeling commands of several commercial CAD systems are analyzed. Those commands are classified and a set of standard modeling commands has been defined. Mapping relations between the standard modeling commands and the native modeling commands of commercial CAD systems are defined. The scope of the current version is limited to parts modeling, not assemblies.

Parametric Empirical Bayes Estimators with Item-Censored Data

  • Choi, Dal-Woo
    • Journal of the Korean Data and Information Science Society
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    • 제8권2호
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    • pp.261-270
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    • 1997
  • This paper is proposed the parametric empirical Bayes(EB) confidence intervals which corrects the deficiencies in the naive EB confidence intervals of the scale parameter in the Weibull distribution under item-censoring scheme. In this case, the bootstrap EB confidence intervals are obtained by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive EB confidence intervals through Monte Carlo study are also presented.

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Identification of Topological Entities and Naming Mapping for Parametric CAD Model Exchanges

  • Mun, Duh-Wan;Han, Soon-Hung
    • International Journal of CAD/CAM
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    • 제5권1호
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    • pp.69-81
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    • 2005
  • As collaborative design and configuration design gain increasing importance in product development, it becomes essential to exchange parametric CAD models among participants. Parametric CAD models can be represented and exchanged in the form of a macro file or a part file that contains the modeling history of a product. The modeling history of a parametric CAD model contains feature specifications and each feature has selection information that records the name of the referenced topological entities. Translating this selection information requires solving the problems of how to identify the referenced topological entities of a feature (persistent naming problem) and how to convert the selection information into the format of the receiving CAD system (naming mapping problem). The present paper introduces the problem of exchanging parametric CAD models and proposes a solution to naming mapping.

Non-parametric 알고리즘을 이용한 신호의 DOA 추정 (DOA estimation of signals using non-parametric algorithm)

  • 이광식;문성익;양두영
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 I
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    • pp.121-124
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    • 2003
  • In this paper, the non-parametric algorithm to estimate DOA(Direction Of Arrival) of signals is proposed and compared with the multidimensional MUSIC algorithm. This non-parametric algorithm with regularizing sparsity constraints achieves super-resolution and noise suppression, effectively. Also, this algorithm offers the increased resolution and significantly reduced sidelobes.

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Semiparametric mixture of experts with unspecified gate network

  • Jung, Dahai;Seo, Byungtae
    • Journal of the Korean Data and Information Science Society
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    • 제28권3호
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    • pp.685-695
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    • 2017
  • The traditional mixture of experts (ME) modeled the gate network using a certain parametric function. However, if the assumed parametric function does not properly reflect the true nature, the prediction strength of ME would become weak. For example, the parametric ME often uses logistic or multinomial logistic models for the network model. However, this could be very misleading if the true nature of the data is quite different from those models. Although, in this case, we may develop more flexible parametric models by extending the model at hand, we will never be free from such misspecification problems. In order to alleviate such weakness of the parametric ME, we propose to use the semi-parametric mixture of experts (SME) in which the gate network is estimated in a non-parametrical way. Based on this, we compared the performance of the SME with those of ME and neural networks via several simulation experiments and real data examples.

Geometric Fitting of Parametric Curves and Surfaces

  • Ahn, Sung-Joon
    • Journal of Information Processing Systems
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    • 제4권4호
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    • pp.153-158
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    • 2008
  • This paper deals with the geometric fitting algorithms for parametric curves and surfaces in 2-D/3-D space, which estimate the curve/surface parameters by minimizing the square sum of the shortest distances between the curve/surface and the given points. We identify three algorithmic approaches for solving the nonlinear problem of geometric fitting. As their general implementation we describe a new algorithm for geometric fitting of parametric curves and surfaces. The curve/surface parameters are estimated in terms of form, position, and rotation parameters. We test and evaluate the performances of the algorithms with fitting examples.

Algorithms of the Parametric Adaptation of Models of Complex Systems by Discrete Observations

  • Radjabov, Bakhtiyor;Khidirova, Charos
    • Journal of Multimedia Information System
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    • 제4권4호
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    • pp.317-320
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    • 2017
  • This paper examines approaches to the development of algorithms of parametric identification of models of complex systems from discrete observations. A modification of a known algorithm Kaczmarz which is designed for closed systems with perturbations, based on the methods of random search and investigates their statistical properties.

멀티채널 오디오 신호의 계층적 코딩이 가능한 파라메트릭 스테레오 코딩 방법에 대한 연구 (Study on novel hierarchical parametric stereo coding method for Multichannel audio signal)

  • 문한길
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.875-876
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    • 2008
  • Parametric stereo coding is a technique to efficiently code a stereo audio signal as a monaural signal plus small amount of parametric overhead to describe the stereo image. The stereo properties are analyzed, encoded, and reinstated in a decoder according to spatial psycho-acoustical principles. However, coding of multichannel audio signal using parametric stereo still requires considerable bit-rate. In this paper, enhanced parametric stereo coding for multichannel audio signal is proposed.

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