• Title/Summary/Keyword: Parametric Method

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Object Audio Coding Standard SAOC Technology and Application (객체 오디오 부호화 표준 SAOC 기술 및 응용)

  • Oh, Hyen-O;Jung, Yang-Won
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.5
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    • pp.45-55
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    • 2010
  • Object-based audio coding technology has been interested with its expectation to apply in wide areas. Recently, ISO/IEC MPEG has standardized a parametric object audio coding method, the SAOC (Spatial Audio Object Coding). This paper introduces parametric object audio coding techniques with special focus on the MPEG SAOC and also describes several issues and solutions that should be considered for a success in its application.

A NEW NON-PARAMETRIC APPROACH TO DETERMINE PROPER MOTIONS OF STAR CLUSTERS

  • PRIYATIKANTO, RHOROM;ARIFYANTO, MOCHAMAD IKBAL
    • Publications of The Korean Astronomical Society
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    • v.30 no.2
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    • pp.271-273
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    • 2015
  • The bulk motion of star clusters can be determined after careful membership analysis using parametric or non-parametric approaches. This study aims to implement non-parametric membership analysis based on Binned Kernel Density Estimators which takes into account measurements errors (simply called BKDE-e) to determine the average proper motion of each cluster. This method is applied to 178 selected star clusters with angular diameters less than 20 arcminutes. Proper motion data from UCAC4 are used for membership determination. Non-parametric analysis using BKDE-e successfully determined the average proper motion of 129 clusters, with good accuracy. Compared to COCD and NCOVOCC, there are 79 clusters with less than $3{\sigma}$ difference. Moreover, we are able to analyse the distribution of the member stars in vector point diagrams which is not always a normal distribution.

Linearized Methods for Quantitative Analysis and Parametric Mapping of Brain PET (뇌 PET 영상 정량화 및 파라메터영상 구성을 위한 선형분석기법)

  • Kim, Su-Jin;Lee, Jae-Sung
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.2
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    • pp.78-84
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    • 2007
  • Quantitative analysis of dynamic brain PET data using a tracer kinetic modeling has played important roles in the investigation of functional and molecular basis of various brain diseases. Parametric imaging of the kinetic parameters (voxel-wise representation of the estimated parameters) has several advantages over the conventional approaches using region of interest (ROI). Therefore, several strategies have been suggested to generate the parametric images with a minimal bias and variability in the parameter estimation. In this paper, we will review the several approaches for parametric imaging with linearized methods which include graphical analysis and mulilinear regression analysis.

Detection and parametric identification of structural nonlinear restoring forces from partial measurements of structural responses

  • Lei, Ying;Hua, Wei;Luo, Sujuan;He, Mingyu
    • Structural Engineering and Mechanics
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    • v.54 no.2
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    • pp.291-304
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    • 2015
  • Compared with the identification of linear structures, it is more challenging to conduct identification of nonlinear structure systems, especially when the locations of structural nonlinearities are not clear in structural systems. Moreover, it is highly desirable to develop methods of parametric identification using partial measurements of structural responses for practical application. To cope with these issues, an identification method is proposed in this paper for the detection and parametric identification of structural nonlinear restoring forces using only partial measurements of structural responses. First, an equivalent linear structural system is proposed for a nonlinear structure and the locations of structural nonlinearities are detected. Then, the parameters of structural nonlinear restoring forces at the locations of identified structural nonlinearities together with the linear part structural parameters are identified by the extended Kalman filter. The proposed method simplifies the identification of nonlinear structures. Numerical examples of the identification of two nonlinear multi-story shear frames and a planar nonlinear truss with different nonlinear models and locations are used to validate the proposed method.

Stability of Nonlinear Oscillations of a Thin Cantilever Beam Under Parametric Excitation (매개 가진되는 얇은 외팔보의 비선형 진동 안정성)

  • Bang, Dong-Jun;Lee, Gye-Dong;Jo, Han-Dong;Jeong, Tae-Gun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.2
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    • pp.160-168
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    • 2008
  • This paper presents the study on the stability of nonlinear oscillations of a thin cantilever beam subject to harmonic base excitation in vertical direction. Two partial differential governing equations under combined parametric and external excitations were derived and converted into two-degree-of-freedom ordinary differential Mathieu equations by using the Galerkin method. We used the method of multiple scales in order to analyze one-to-one combination resonance. From these, we could obtain the eigenvalue problem and analyze the stability of the system. From the thin cantilever experiment using foamax, we could observe the nonlinear modes of bending, twisting, sway, and snap-through buckling. In addition to qualitative information, the experiment using aluminum gave also the quantitative information for the stability of combination resonance of a thin cantilever beam under parametric excitation.

Testing the Equality of Several Correlation Coefficients by Permutation Method

  • Um, Yonghwan
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.6
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    • pp.167-174
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    • 2022
  • In this paper we investigate the permutation test for the equality of correlation coefficients in several independent populations. Permutation test is a non-parametric testing methodology based upon the exchangeability of observations. Exchangeability is a generalization of the concept of independent, identically distributed random variables. Using permutation method, we may construct asymptotically exact test. This method is asymptotically as powerful as standard parametric tests and is a valuable tool when the sample sizes are small and normality assumption cannot be met. We first review existing parametric approaches to test the equality of correlation coefficients and compare them with the permutation test. At the end, all the approaches are illustrated using Iris data example.

A Study on Statistical Classification of Wear Debris Morphology

  • Cho, Unchung
    • KSTLE International Journal
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    • v.2 no.1
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    • pp.35-39
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    • 2001
  • In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

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Geometric Modeling and Five-axis Machining of Tire Master Models

  • Lee, Cheol-Soo
    • International Journal of Precision Engineering and Manufacturing
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    • v.9 no.3
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    • pp.75-78
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    • 2008
  • Tire molds are manufactured by aluminum casting, direct five-axis machining, and electric discharging machining. Master models made of chemical wood are necessary if aluminum casting is used. They are designed with a three-dimensional computer-aided design system and milled by a five-axis machine. In this paper, a method for generating and machining a tire surface model is proposed and demonstrated. The groove surfaces, which are the main feature of the tire model, are created using a parametric design concept. An automatically programmed tool-like descriptive language is presented to implement the parametric design. Various groove geometries can be created by changing variables. For convenience, groove surfaces and raw cutter location (CL) data are generated in two-dimensional drawing space. The CL data are mapped to the tread surface to obtain five-axis CL data to machine the master model. The proposed method was tested by actual milling using the five-axis control machine. The results demonstrate that the method is useful for manufacturing a tire mold.

Added resistance and parametric roll prediction as a design criteria for energy efficient ships

  • Somayajula, Abhilash;Guha, Amitava;Falzarano, Jeffrey;Chun, Ho-Hwan;Jung, Kwang Hyo
    • Ocean Systems Engineering
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    • v.4 no.2
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    • pp.117-136
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    • 2014
  • The increased interest in the design of energy efficient ships post IMO regulation on enforcing EEDI has encouraged researchers to reevaluate the numerical methods in predicting important hull design parameters. The prediction of added resistance and stability of ships in the rough sea environment dictates selection of ship hulls. A 3D panel method based on Green function is developed for vessel motion prediction. The effects of parametric instability are also investigated using the Volterra series approach to model the hydrostatic variation due to ship motions. The added resistance is calculated using the near field pressure integration method.

A General Semiparametric Additive Risk Model

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.2
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    • pp.421-429
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    • 2008
  • We consider a general semiparametric additive risk model that consists of three components. They are parametric, purely and smoothly nonparametric components. In parametric component, time dependent term is known up to proportional constant. In purely nonparametric component, time dependent term is an unknown function, and time dependent term in smoothly nonparametric component is an unknown but smoothly function. As an estimation method of this model, we use the weighted least square estimation by Huffer and McKeague (1991). We provide an illustrative example as well as a simulation study that compares the performance of our method with the ordinary least square method.

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