• 제목/요약/키워드: Radial Gradient

검색결과 221건 처리시간 0.024초

Nonlocal geometrically nonlinear dynamic analysis of nanobeam using a meshless method

  • Ghadiri Rad, Mohammad Hossein;Shahabian, Farzad;Hosseini, Seyed Mahmoud
    • Steel and Composite Structures
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    • 제32권3호
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    • pp.293-304
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    • 2019
  • In the present paper, the element free Galerkin (EFG) method is developed for geometrically nonlinear analysis of deep beams considering small scale effect. To interpret the behavior of structure at the nano scale, the higher-order gradient elasticity nonlocal theory is taken into account. The radial point interpolation method with high order of continuity is used to construct the shape functions. The nonlinear equation of motion is derived using the principle of the minimization of total potential energy based on total Lagrangian approach. The Newmark method with the small time steps is used to solve the time dependent equations. At each time step, the iterative Newton-Raphson technique is applied to minimize the residential forces caused by the nonlinearity of the equations. The effects of nonlocal parameter and aspect ratio on stiffness and dynamic parameters are discussed by numerical examples. This paper furnishes a ground to develop the EFG method for large deformation analysis of structures considering small scale effects.

Human and Robot Tracking Using Histogram of Oriented Gradient Feature

  • Lee, Jeong-eom;Yi, Chong-ho;Kim, Dong-won
    • Journal of Platform Technology
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    • 제6권4호
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    • pp.18-25
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    • 2018
  • This paper describes a real-time human and robot tracking method in Intelligent Space with multi-camera networks. The proposed method detects candidates for humans and robots by using the histogram of oriented gradients (HOG) feature in an image. To classify humans and robots from the candidates in real time, we apply cascaded structure to constructing a strong classifier which consists of many weak classifiers as follows: a linear support vector machine (SVM) and a radial-basis function (RBF) SVM. By using the multiple view geometry, the method estimates the 3D position of humans and robots from their 2D coordinates on image coordinate system, and tracks their positions by using stochastic approach. To test the performance of the method, humans and robots are asked to move according to given rectangular and circular paths. Experimental results show that the proposed method is able to reduce the localization error and be good for a practical application of human-centered services in the Intelligent Space.

Simulation and modeling for stability analysis of functionally graded non-uniform pipes with porosity-dependent properties

  • Peng Zhang;Jun Song;Tayebeh Mahmoudi
    • Steel and Composite Structures
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    • 제48권2호
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    • pp.235-250
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    • 2023
  • The present paper examines the stability analysis of the buckling differentiae of the small-scale, non-uniform porosity-dependent functionally graded (PD-FG) tube. The high-order beam theory and nonlocal strain gradient theory are operated for the mathematical modeling of nanotubes based on the Hamilton principle. In this paper, the external radius function is non-uniform. In contrast, the internal radius is uniform, and the cross-section changes along the tube length due to these radius functions based on the four types of useful mathematical functions. The PD-FG material distributions are varied in the radial direction and made with ceramics and metals. The governing partial differential equations (PDEs) and associated boundary conditions are solved via a numerical method for different boundary conditions. The received outcomes concerning different presented parameters are valuable to the design and production of small-scale devices and intelligent structures.

THEORETICAL STUDY ON OBSERVED COLOR-MAGNITUDE DIAGRAMS

  • Lee, See-Woo
    • 천문학회지
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    • 제12권1호
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    • pp.41-70
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    • 1979
  • From $B\ddot{o}hm$-Vitense's atmospheric model calculations, the relations, [$T_e$, (B-V)] and [B.C, (B-V)] with respect to heavy element abundance were obtained. Using these relations and evolutionary model calculations of Rood, and Sweigart and Gross, analytic expressions for some physical parameters relating to the C-M diagrams of globular clusters were derived, and they were applied to 21 globular clusters with observed transition periods of RR Lyrae variables. More than 20 different parameters were examined for each globular cluster. The derived ranges of some basic parameters are as follows; $Y=0.21{\sim}0.33,\;Z=1.5{\times}10^{-4}{\sim}4.5{\times}10^{-3},\;age,\;t=9.5{\sim}19{\times}10^9$ years, mass for red giants, $m_{RG}=0.74m_{\odot}{\sim}0.91m_{\odot}$, mass for RR Lyrae stars, $m_{RR}=0.59m_{\odot}{\sim}0.75m_{\odot}$, the visual magnitude difference between the turnoff point and the horizontal branch (HB), ${\Delta}V_{to}=3.1{\sim}3.4(<{\Delta}V_{to}>=3.32)$, the color of the blue edge of RR Lyrae gap, $(B-V)_{BE}=0.17{\sim}0.21=(<(B-V)_{BE}>=0.18),\;[\frac{m}{L}]_{RR}=-1.7{\sim}-1.9$, mass difference of $m_{RR}$ relative to $m_{RG},(m_{RG}-m_{RR})/m_{RG}=0.0{\sim}0.39$. It was found that the ranges of derived parameters agree reasonably well with the observed ones and those estimated by others. Some important results obtained herein can be summarized as follows; (i) There are considerable variations in the initial helium abundance and in age of globular clusters. (ii) The radial gradient of heavy element abundance does exist for globular clusters as shown by Janes for field stars and open clusters. (iii) The helium abundance seems to have been increased with age by massive star evolution after a considerable amount (Y>0.2) of helium had been attained by the Big-Bang nucleosynthesis, but there is not seen a radial gradient of helium abundance. (iv) A considerable amount of heavy elements ($Z{\sim}10{-3}$) might have been formed in the inner halo ($r_{GC}$<10 kpc) from the earliest galactic co1lapse, and then the heavy element abundance has been slowly enriched towards the galactic center and disk, establishing the radial gradient of heavy element abundance. (v) The final galactic disk formation might have taken much longer by about a half of the galactic age than the halo formation, supporting a slow, inhomogeneous co1lapse model of Larson. (vi) Of the three principal parameters controlling the morphology of C-M diagrams, it was found that the first parameter is heavy clement abundance, the second age and the third helium abundance. (vii) The globular clusters can be divided into three different groups, AI, BI and CII according to Z, Y an d age as well as Dickens' HB types. BI group clusters of HB types 4 and 5 like M 3 and NGC 7006 are the oldest and have the lowest helium abundance of the three groups. And also they appear in the inner halo. On the other hand, the youngest AI clusters have the highest Z and Y, and appear in the innermost halo region and in the disk. (viii) From the result of the clean separations of the clusters into three groups, a three dimensional classification with three parameters, Z, Y and age is prsented. (ix) The anomalous C-M diagrams can be expalined in terms of the three principal parameters. That is, the anomaly of NGC 362 and NGC 7006 is accounted for by the smaller age of the order of $1{\sim}2{\times}10^9$ years rather than by the helium abundance difference, compared with M 3. (x) The difference in two Oosterhoff types I and II can be explained in terms of the mean mass difference of RR Lyrae variables rather than in terms of the helium abundance difference as suggested by Stobie. The mean mass of the variables in Oosterhoff type I clusters is smaller by $0.074m_{\odot}$ which is exactly consistent with Rood's estimate. Since it was found that the mean mass of RR Lyrae stars increases with decreasing Z, the two Oosterhoff types can be explained substantially by the metal abundance difference; the type II has Z<$3.4{\times}10^{-4}$, and the type I has higher Z than the type II.

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다항식 방사형기저함수 신경회로망을 이용한 ASP 모델링 및 시뮬레이터 설계 (Design of Modeling & Simulator for ASP Realized with the Aid of Polynomiai Radial Basis Function Neural Networks)

  • 김현기;이승주;오성권
    • 전기학회논문지
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    • 제62권4호
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    • pp.554-561
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    • 2013
  • In this paper, we introduce a modeling and a process simulator developed with the aid of pRBFNNs for activated sludge process in the sewage treatment system. Activated sludge process(ASP) of sewage treatment system facilities is a process that handles biological treatment reaction and is a very complex system with non-linear characteristics. In this paper, we carry out modeling by using essential ASP factors such as water effluent quality, the manipulated value of various pumps, and water inflow quality, and so on. Intelligent algorithms used for constructing process simulator are developed by considering multi-output polynomial radial basis function Neural Networks(pRBFNNs) as well as Fuzzy C-Means clustering and Particle Swarm Optimization. Here, the apexes of the antecedent gaussian functions of fuzzy rules are decided by C-means clustering algorithm and the apexes of the consequent part of fuzzy rules are learned by using back-propagation based on gradient decent method. Also, the parameters related to the fuzzy model are optimized by means of particle swarm optimization. The coefficients of the consequent polynomial of fuzzy rules and performance index are considered by the Least Square Estimation and Mean Squared Error. The descriptions of developed process simulator architecture and ensuing operation method are handled.

움직임 추정 능동 방사선 기반 고속 객체 추적 (Motion-Estimated Active Rays-Based Fast Moving Object Tracking)

  • 라정중;서경석;최흥문
    • 대한전자공학회논문지SP
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    • 제42권3호
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    • pp.15-22
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    • 2005
  • 객체 중심점에서 움직임을 추정하여 빠르게 이동하는 객체의 윤곽선을 추적 할 수 있는 알고리듬을 제안하였다. 방사상 표현(radial representation) 방식을 적용하여 객체 중심점에서만 블록정합 (block matching) 알고리듬으로 움직임을 추정하여 적은 계산량으로 객체 움직임을 추정함으로써 객체 윤곽선을 추적하였다. 객체의 움직임을 추정함으로써 프레임 간 객체의 움직임이 객체 중심에서 윤곽까지 거리 이상 빠르게 이동하는 객체도 추적할 수 있다. 에너지 수렴 과정에서 기울기 영상과 차영상(difference image)을 에너지 함수로 함께 사용함으로 복잡한 배경 등에도 강건하도록 하였다. 실험 결과 움직임이 빠른 객체와 복잡한 배경 속의 객체도 실시간으로 강건하게 추적함을 확인하였다.

시스템 모델링을 위한 일반화된 RBF 신경회로망의 온라인 구성 (An On-line Construction of Generalized RBF Networks for System Modeling)

  • 권오신;김형석;최종수
    • 전자공학회논문지CI
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    • 제37권1호
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    • pp.32-42
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    • 2000
  • 이 논문에서는 비선형 시스템 모델링을 위한 일반화된 RBF 신경회로망(GRBFN)을 순차적으로 구성하기 위한 온라인 학습 알고리즘을 제안한다. 상수 연결강도를 갖는 표준 RBF 신경회로망의 확장형인GRBFN은 여러 개의 국부 선형모델을 결합하여 비선형 시스템을 표현할 수 있는 구조이다. 제안한 학습 알고리즘은 구조 학습과 파라미터 학습을 수행하는 두 단계의 학습으로 구성된다. 구조 학습은 주어진 훈련 데이터로부터 새로운 은닉 유니트 및 선형 국부모델을 할항하기 위하여 훈련 오차와 Mahalanobis 거리에 기초한 두 개의 생성 조건을 이용하여 GRBFN 모델을 구성한다. 파라미터 학습은 경사강하 법칙을 기반으로 기존 네트웍의 파라미터 벡터를 갱신한다. 제안한 알고리즘의 모델링 성능을 평가하기 위해서 잘 알려진 두 예제에 대한 시뮬레이션 및 결과를 제시한다.

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Comparison of the PSD radial profiles between before and after geosynchronous flux dropout: case studies using THEMIS observations

  • 황정아;이대영;김경찬;최은진;신대규;김진희;조정희
    • 천문학회보
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    • 제37권2호
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    • pp.122-122
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    • 2012
  • Geosynchronous electron flux dropouts are most likely due to fast drift loss of the particles to the magnetopause (or equivalently, the "magnetopause shadowing effect"). A possible effect related to the drift loss is the radial diffusion of PSD due to gradient of PSD set by the drift loss effect at an outer L region. This possibly implies that the drift loss can affect the flux levels even inside the trapping boundary. We recently investigated the details of such diffusion process by solving the diffusion equation with a set of initial and boundary conditions set by the drift loss. Motivated by the simulation work, we have examined observationally the energy spectrum and pitch angle distribution near trapping boundary during the geosynchronous flux dropouts. For this work, we have first identified a list of geosynchronous flux dropout events for 2007-2010 from GOES satellite electron measurements and solar wind pressures observed by ACE satellite. We have then used the electron data from the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft measurements to investigate the particle fluxes. The five THEMIS spacecraft sufficiently cover the inner magnetospheric regions near the equatorial plane and thus provide us with data of much higher spatial resolution. In this paper, we report some case studies showing energy dependence during magnetopause shadowing effect.

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PCA와 LDA를 결합한 데이터 전 처리와 다항식 기반 RBFNNs을 이용한 얼굴 인식 알고리즘 설계 (Design of Face Recognition algorithm Using PCA&LDA combined for Data Pre-Processing and Polynomial-based RBF Neural Networks)

  • 오성권;유성훈
    • 전기학회논문지
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    • 제61권5호
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    • pp.744-752
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    • 2012
  • In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.

기상레이더를 이용한 뉴로-퍼지 알고리즘 기반 에코 분류기 설계 (Design of Echo Classifier Based on Neuro-Fuzzy Algorithm Using Meteorological Radar Data)

  • 오성권;고준현
    • 전기학회논문지
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    • 제63권5호
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    • pp.676-682
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    • 2014
  • In this paper, precipitation echo(PRE) and non-precipitaion echo(N-PRE)(including ground echo and clear echo) through weather radar data are identified with the aid of neuro-fuzzy algorithm. The accuracy of the radar information is lowered because meteorological radar data is mixed with the PRE and N-PRE. So this problem is resolved by using RBFNN and judgement module. Structure expression of weather radar data are analyzed in order to classify PRE and N-PRE. Input variables such as Standard deviation of reflectivity(SDZ), Vertical gradient of reflectivity(VGZ), Spin change(SPN), Frequency(FR), cumulation reflectivity during 1 hour(1hDZ), and cumulation reflectivity during 2 hour(2hDZ) are made by using weather radar data and then each characteristic of input variable is analyzed. Input data is built up from the selected input variables among these input variables, which have a critical effect on the classification between PRE and N-PRE. Echo judgment module is developed to do echo classification between PRE and N-PRE by using testing dataset. Polynomial-based radial basis function neural networks(RBFNNs) are used as neuro-fuzzy algorithm, and the proposed neuro-fuzzy echo pattern classifier is designed by combining RBFNN with echo judgement module. Finally, the results of the proposed classifier are compared with both CZ and DZ, as well as QC data, and analyzed from the view point of output performance.