• Title/Summary/Keyword: Polynomial Function

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Comparison of Various Shear Deformation Functions for Laminated Composite/Sandwich Plates (복합적층 및 샌드위치판 전단변형함수에 관한 상호비교연구)

  • Park, Won-Tae;Chang, Suk-Yoon;Chun, Kyoung-Sik
    • Journal of the Korean Society for Advanced Composite Structures
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    • v.1 no.3
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    • pp.1-9
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    • 2010
  • In this paper, we used various shear deformation functions for modelling isotropic, symmetric composite and sandwich plates discretized by a mixed finite element method based on the Lagrangian/Hermite interpolation functions. These shear deformation theories uses polynomial, trigonometric, hyperbolic and exponential functions through the thickness direction, allowing for zero transverse shear stresses at the top and bottom surfaces of the plate. All shear deformation functions are compared with other available analytical/3D elasticity solutions, are predicted the reasonable accuracy for investigated problems. Particularly, The present results show that the use of exponential shear deformation theory (Karama et al. 2003; Aydogu 2009) provides very good solutions for composite and sandwich plates.

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Estimation of Sensible and Latent Heat Fluxes Using the Satellite and Buoy Data (위성과 부이자료를 이용한 현.잠열 추정에 관한 연구)

  • 홍기만;김영섭;윤홍주;박경원
    • Proceedings of the KSRS Conference
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    • 2001.03a
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    • pp.104-110
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    • 2001
  • Ocean heat fluxes over a wide region are generally estimated by an aerodynamic bulk fromula. Though a remote sensing technique can be expected to estimated global heat flux, it is difficult to obtain air temperature and specific humidity at sea surface by a remote sensor. In this study present a new method with which to determine near-sea surface air temperature from in situ data. Also, These methods compared with other methods. A new method used a linear regression equation between sea surface temperature and air temperature of the buoys data. In this study new method is validated using observed monthly mean data at the Japan Meteorological Agency(JMA), National Data Buoy Center(NDBC) and Tropical Ocean-Global Atmosphere(TOGA)-Tropical Atmosphere Ocean(TAO) buoys. The result that bias and rmse are 0.28, 1.5$0^{\circ}C$ respectively. The correlation coefficient is 0.98. Also, to retrieve near-sea surface specific humidity(Q) from good nonlinear regression relationship between vapor pressure(Ea) of buoy data and air temperature, after obtained the third-order polynomial function, compared with that of estimated from SSM/I empirical equation by Schussel et al(1995). The result that bias and rmse are -1.42 and 1.75(g/kg).

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RBFNNs-based Recognition System of Vehicle License Plate Using Distortion Correction and Local Binarization (왜곡 보정과 지역 이진화를 이용한 RBFNNs 기반 차량 번호판 인식 시스템)

  • Kim, Sun-Hwan;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.9
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    • pp.1531-1540
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    • 2016
  • In this paper, we propose vehicle license plate recognition system based on Radial Basis Function Neural Networks (RBFNNs) with the use of local binarization functions and canny edge algorithm. In order to detect the area of license plate and also recognize license plate numbers, binary images are generated by using local binarization methods, which consider local brightness, and canny edge detection. The generated binary images provide information related to the size and the position of license plate. Additionally, image warping is used to compensate the distortion of images obtained from the side. After extracting license plate numbers, the dimensionality of number images is reduced through Principal Component Analysis (PCA) and is used as input variables to RBFNNs. Particle Swarm Optimization (PSO) algorithm is used to optimize a number of essential parameters needed to improve the accuracy of RBFNNs. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. Image data sets are obtained by changing the distance between stationary vehicle and camera and then used to evaluate the performance of the proposed system.

Numerical Study on Pulverized Coal Combustion Applying Two-Phase WSGGM (이상 회체가스 가중합산모델을 적용한 미분탄 연소의 수치적 연구)

  • Yu, Myoung-Jong;Kang, Shin-Jae;Baek, Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.24 no.10
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    • pp.1368-1379
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    • 2000
  • A numerical study on swirling pulverized coal combustion in an axisymmetric enclosure is carried out by applying the 2-phase weighted sum of gray gases model (WSGGM) approach with the discrete ordinate method (DOM) to model the radiative heat transfer equation. In the radiative transfer equation, the same polynomial equation and coefficients for weighting factors as those for gas are adopted for the coal/char particles as a function of partial pressure and particle temperature. The Eulerian balance equations for mass, momentum, energy, and species mass fractions are adopted with the standard and RNG k-${\varepsilon}$ turbulence model, whereas the Lagrangian approach is used for the particulate phase. The eddy-dissipation model is employed for the reaction rate for gaseous mixture, and the single-step and two-step first-order reaction model for the devolatilization process for coal. Special attention is given to establish the thermal boundary conditions on radiative transfer equation By comparing the numerical results with experimental ones, the radiation model used here is confirmed and found to provide an alternative for simulating the radiative transfer.

Counting Process of MAP(3)s and Moment Fittings (3계 마코프 도착과정의 계수과정과 적률근사)

  • Kim, Sunkyo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.42 no.1
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    • pp.19-28
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    • 2017
  • Moments of stationary intervals and those of the counting process can be used for moment fittings of the point processes. As for the Markovian arrival processes, the moments of stationary intervals are given as a polynomial function of parameters whereas the moments of the counting process involve exponential terms. Therefore, moment fittings are more complicated with the counting process than with stationary intervals. However, in queueing network analysis, cross-correlation between point processes can be modeled more conveniently with counting processes than with stationary intervals. A Laplace-Stieltjies transform of the stationary intervals of MAP (3)s is recently proposed in minimal number of parameters. We extend the results and present the Laplace transform of the counting process of MAP (3)s. We also show how moments of the counting process such as index of dispersions for counts, IDC, and limiting IDC can be used for moment fittings. Examples of exact MAP (3) moment fittings are also presented on the basis of moments of stationary intervals and those of the counting process.

Diversity-Multiplexing Tradeoff Analysis of Wireless Multiple-Antenna Cooperative Systems in General Fading Channels

  • Xu, Kun;Gao, Yuanyuan;Yi, Xiaoxin;Zhang, Yajun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.11
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    • pp.3026-3045
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    • 2012
  • In this paper, diversity-multiplexing tradeoff (DMT) of three-user wireless multiple-antenna cooperative systems is investigated in general fading channels when half-duplex and decode-and-forward relay is employed. Three protocols, i.e., adaptive protocol, receive diversity protocol, and dual-hop relaying protocol, are considered. The general fading channels may include transmit and/or receive correlation and nonzero channel means, and are extensions of independent and identically distributed Rayleigh or Rician fading channels. Firstly, simple DMT expressions are derived for general fading channels with zero channel means and no correlation when users employ arbitrary number of antennas. Explicit DMT expressions are also obtained when all users employ the same number of antennas and the channels between any two users are of the same fading statistics. Finally, the impact of nonzero channel means and/or correlation on DMT is evaluated. It is revealed theoretically that the DMTs depend on the number of antennas at each user, channel means (except for Rayleigh and Rician fading statistics), transmit and/or receive correlation, and the polynomial behavior near zero of the channel gain probability density function. Examples are also provided to illustrate the analysis and results.

Adaptive p-finite element method for wind engineering

  • Selvam, R. Panneer;Qu, Zu-Qing
    • Wind and Structures
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    • v.5 no.2_3_4
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    • pp.301-316
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    • 2002
  • An important goal of computational wind engineering is to impact the design process with simulations of flow around buildings and bridges. One challenging aspect of this goal is to solve the Navier-Stokes (NS) equations accurately. For the unsteady computations, an adaptive finite element technique may reduce the computer time and storage. The preliminary application of a p-version as well as an h-version adaptive technique to computational wind engineering has been reported in previous paper. The details on the implementation of p-adaptive technique will be discussed in this paper. In this technique, two posteriori error estimations, which are based on the velocity and vorticity, are first presented. Then, the polynomial order of the interpolation function is increased continuously element by element until the estimated error is less than the accepted. The second through sixth orders of hierarchical functions are used as the interpolation polynomials. Unequal order interpolations are used for velocity and pressure. Using the flow around a circular cylinder with Reynolds number of 1000 the two error estimators are compared. The result show that the estimated error based on the velocity is lower than that based on the vorticity.

Prediction of negative peak wind pressures on roofs of low-rise building

  • Rao, K. Balaji;Anoop, M.B.;Harikrishna, P.;Rajan, S. Selvi;Iyer, Nagesh R.
    • Wind and Structures
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    • v.19 no.6
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    • pp.623-647
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    • 2014
  • In this paper, a probability distribution which is consistent with the observed phenomenon at the roof corner and, also on other portions of the roof, of a low-rise building is proposed. The model is consistent with the choice of probability density function suggested by the statistical thermodynamics of open systems and turbulence modelling in fluid mechanics. After presenting the justification based on physical phenomenon and based on statistical arguments, the fit of alpha-stable distribution for prediction of extreme negative wind pressure coefficients is explored. The predictions are compared with those actually observed during wind tunnel experiments (using wind tunnel experimental data obtained from the aerodynamic database of Tokyo Polytechnic University), and those predicted by using Gumbel minimum and Hermite polynomial model. The predictions are also compared with those estimated using a recently proposed non-parametric model in regions where stability criterion (in skewness-kurtosis space) is satisfied. From the comparisons, it is noted that the proposed model can be used to estimate the extreme peak negative wind pressure coefficients. The model has an advantage that it is consistent with the physical processes proposed in the literature for explaining large fluctuations at the roof corners.

A study of a cardiac disorder distinction based on SVM by using a heart sound (심음을 이용한 SVM 기반의 심장 질환 판별에 관한 연구)

  • Kim, Bo-Ri;Beack, Seung-Hwa;Kim, Dong-Wan;Paek, Seung-Eun;Kwon, Sun-Tae
    • Proceedings of the KIEE Conference
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    • 2006.07d
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    • pp.2173-2174
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    • 2006
  • 심음은 심장이 수축, 확장 시에 심장의 움직임과 혈류의 흐름에 의해 발생하는 음향이다. 심음은 여러 신호원으로 이루어져 있고, 매우 복잡하고 비고정적인 신호이다. 심장의 질환에 따라 심음의 소리는 다르게 나타난다. 심음을 구분하여 심장 질환의 유무를 판단하는 가장 기초적인 기준이 될 수 있다. 본 연구에서는 Support Vector Machine 기법을 이용하여 심음을 통한 심장 질환 판별 검출 알고리즘을 제안하였다. Support Vector Machine은 신경망의 한 종류이며 이진분류에서 좋은 성능을 보인다. 또한 Polynomial Radial Basis Function, Multi-Layer Perceptron Classifiers를 위한 대안적인 학습방법으로 사용된다. 이러한 특성을 사용하여 심음의 데이터들을 일정한 기준에 의하여 (+)데이터와 (-)데이터로 분리한 후, 각 데이터들을 학습시켜 최적의 데이터를 만든다. 이후 각 데이터들은 점층적인 추가 학습을 시킴으로써 적은 양의 학습 데이터만으로도 높은 분류 성능을 표현할 수 있다. 이 연구에서 제안된 SVM을 실제 심음 데이터에 적용한 실험에서 심장 질환의 유무 판별에 우수한 성능을 보임을 확인할 수 있을 것으로 판단된다.

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Implementation of Adaptive Hierarchical Fair Com pet ion-based Genetic Algorithms and Its Application to Nonlinear System Modeling (적응형 계층적 공정 경쟁 기반 병렬유전자 알고리즘의 구현 및 비선형 시스템 모델링으로의 적용)

  • Choi, Jeoung-Nae;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.120-122
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    • 2006
  • The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

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