• Title/Summary/Keyword: conjugate point

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Adjustment of Exterior Orientation of the Digital Aerial Images using LiDAR Points

  • Yoon, Jong-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.5
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    • pp.485-491
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    • 2008
  • LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

Bayesian Multiple Change-Point Estimation and Segmentation

  • Kim, Jaehee;Cheon, Sooyoung
    • Communications for Statistical Applications and Methods
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    • v.20 no.6
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    • pp.439-454
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    • 2013
  • This study presents a Bayesian multiple change-point detection approach to segment and classify the observations that no longer come from an initial population after a certain time. Inferences are based on the multiple change-points in a sequence of random variables where the probability distribution changes. Bayesian multiple change-point estimation is classifies each observation into a segment. We use a truncated Poisson distribution for the number of change-points and conjugate prior for the exponential family distributions. The Bayesian method can lead the unsupervised classification of discrete, continuous variables and multivariate vectors based on latent class models; therefore, the solution for change-points corresponds to the stochastic partitions of observed data. We demonstrate segmentation with real data.

Effect of a chemical reaction on magnetohydrodynamic (MHD) stagnation point flow of Walters-B nanofluid with newtonian heat and mass conditions

  • Qayyum, Sajid;Hayat, Tasawar;Shehzad, Sabir A.;Alsaedi, Ahmed
    • Nuclear Engineering and Technology
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    • v.49 no.8
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    • pp.1636-1644
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    • 2017
  • The main purpose of this article is to describe the magnetohydrodynamic stagnation point flow of Walter-B nanofluid over a stretching sheet. The phenomena of heat and mass transfer are based on the involvement of thermal radiation and chemical reaction. Characteristics of Newtonian heating are given special attention. The Brownian motion and thermophoresis models are introduced in the temperature and concentration expressions. Appropriate variables are implemented for the transformation of partial differential frameworks into sets of ordinary differential equations. Plots for velocity, temperature, and nanoparticle concentration are displayed and analyzed for governing parameters. The skin friction coefficient and local Nusselt and Sherwood numbers are studied using numerical values. The temperature and heat transfer rate are enhanced within the frame of the thermal conjugate parameter.

Bayesian Multiple Change-Point Estimation of Multivariate Mean Vectors for Small Data

  • Cheon, Sooyoung;Yu, Wenxing
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.999-1008
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    • 2012
  • A Bayesian multiple change-point model for small data is proposed for multivariate means and is an extension of the univariate case of Cheon and Yu (2012). The proposed model requires data from a multivariate noncentral $t$-distribution and conjugate priors for the distributional parameters. We apply the Metropolis-Hastings-within-Gibbs Sampling algorithm to the proposed model to detecte multiple change-points. The performance of our proposed algorithm has been investigated on simulated and real dataset, Hanwoo fat content bivariate data.

An Efficient Traning of Multilayer Neural Newtorks Using Stochastic Approximation and Conjugate Gradient Method (확률적 근사법과 공액기울기법을 이용한 다층신경망의 효율적인 학습)

  • 조용현
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.5
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    • pp.98-106
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    • 1998
  • This paper proposes an efficient learning algorithm for improving the training performance of the neural network. The proposed method improves the training performance by applying the backpropagation algorithm of a global optimization method which is a hybrid of a stochastic approximation and a conjugate gradient method. The approximate initial point for f a ~gtl obal optimization is estimated first by applying the stochastic approximation, and then the conjugate gradient method, which is the fast gradient descent method, is applied for a high speed optimization. The proposed method has been applied to the parity checking and the pattern classification, and the simulation results show that the performance of the proposed method is superior to those of the conventional backpropagation and the backpropagation algorithm which is a hyhrid of the stochastic approximation and steepest descent method.

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Area based image matching with MOC-NA imagery (MOC-NA 영상의 영역기준 영상정합)

  • Youn, Jun-Hee;Park, Choung-Hwan
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.4
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    • pp.463-469
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    • 2010
  • Since MOLA(Mars Orbiter Laser Altimeter) data, which provides altimetry data for Mars, does not cover the whole Mars area, image matching with MOC imagery should be implemented for the generation of DEM. However, automatic image matching is difficult because of insufficient features and low contrast. In this paper, we present the area based semi-automatic image matching algorithm with MOC-NA(Mars Orbiter Camera ? Narrow Angle) imagery. To accomplish this, seed points describing conjugate points are manually added for the stereo imagery, and interesting points are automatically produced by using such seed points. Produced interesting points being used as initial conjugate points, area based image matching is implemented. For the points which fail to match, the locations of initial conjugate points are recalculated by using matched six points and image matching process is re-implemented. The quality assessment by reversing the role of target and search image shows 97.5 % of points were laid within one pixel absolute difference.

Improving the Training Performance of Neural Networks by using Hybrid Algorithm (하이브리드 알고리즘을 이용한 신경망의 학습성능 개선)

  • Kim, Weon-Ook;Cho, Yong-Hyun;Kim, Young-Il;Kang, In-Ku
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.11
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    • pp.2769-2779
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    • 1997
  • This Paper Proposes an efficient method for improving the training performance of the neural networks using a hybrid of conjugate gradient backpropagation algorithm and dynamic tunneling backpropagation algorithm The conjugate gradient backpropagation algorithm, which is the fast gradient algorithm, is applied for high speed optimization. The dynamic tunneling backpropagation algorithm, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Conversing to the local minima by using the conjugate gradient backpropagation algorithm, the new initial point for escaping the local minima is estimated by dynamic tunneling backpropagation algorithm. The proposed method has been applied to the parity check and the pattern classification. The simulation results show that the performance of proposed method is superior to those of gradient descent backpropagtion algorithm and a hybrid of gradient descent and dynamic tunneling backpropagation algorithm, and the new algorithm converges more often to the global minima than gradient descent backpropagation algorithm.

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REGISTRATION OF IKONOS-2 GEO-LEVEL SATELLITE IMAGERY USING ALS DATA;BY USING LINEAR FEATURES AS REGISTRATION PRIMITIVES

  • Lee, Jae-Bin;Song, Woo-Seok;Lee, Chang-No;Yu, Ki-Yun;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.14-17
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    • 2007
  • To make use of surveying data obtained from different sensors and different techniques in a common reference frame, it is a pre-requite step to register them in a common coordinate system. For this purpose, we have developed a methodology to register IKONOS-2 Satellite Imagery using ALS data. To achieve this, conjugate features from these data should be extracted in advance. In the study, linear features are chosen as conjugate features because they can be accurately extracted from man-made structures in urban area, and more easily than point features from ALS data. Then, observation equations are established from similarity measurements of the extracted features. During the process, considering the characteristics of systematic errors in IKONOS-2 satellite imagery, the transformation function were selected and used. In addition, we also analyzed how the number of linear features and their spatial distribution used as control features affect the accuracy of registration. Finally, the results were evaluated statistically and the results clearly demonstrated that the proposed algorithms are appropriate to register these data.

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Optical Implementation of Incoherent Holographic 3D Display System using Modified Triangular and Mach-Zehender Interferometer (변형된 삼각 및 마하젠더 간섭계 기반의 인코히어런트 홀로그래픽 3D 디스플레이 시스템의 광학적 구현)

  • 김승철;구정식;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.4C
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    • pp.524-532
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    • 2004
  • In this paper, an incoherent holographic 3D imaging and display system based on the modified triangular and Mach-Zehnder interferometers is optically implemented and some experiments are carried out. Incoherent hologram of a 3D object is generated by using the hologram input system of modified triangular interferometer. Then this complex hologram is reconstructed by using the hologram output system of modified Mach-Zehnder interferometer in which two LCD spatial light modulators and a waveplate are inserted. From the experiment with two point sources having a depth difference of 100 mm each other, it is revealed that each point source can be independently reconstructed at its own focal position from the complex hologram, while both of the bias and conjugate image are simultaneously eliminated at the same time. And in the experiment with the real 3D object of two dices having a depth difference of 30 mm each other, it is also conformed that the bias and conjugate image can be effectively eliminated from the hologram pattern and each 3D dice can be also successfully reconstructed at its own focal position from the complex hologram. These experiment results finally suggest a possibility of implementing a new incoherent holographic 3D imaging and display system using the modified triangular and Mach-Zehender interferometers.

Real-Time Implementation of the 8 kbps CS-ACELP (DSP16210을 이용한 8kbps CS-ACELP 의 실시간 구현)

  • 박지현;박성일정원국임병근
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.1211-1214
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    • 1998
  • Real-time implementation of Conjugate-Structure Algebraic CELP(CS-ACELP) is presented. ITU-T Study Group(SG) 15 has standardized the CS-ACELP speech coding algorithm as G.729. A real-time implementation of the CS-ACELP is achieved using 16 bit fixed point DSP16210 Digital Signal Processor (DSP) of Lucent Technologies. The speech coder has been implemented in the bit-exact manner using the fixed point CS-ACELP C source which is the part of the G.729 standard. To provide a multi-channel vocoder solution to digital communication system, we try to minimize the complexity(e.g., MIPS, ROM, RAM) of CS-ACELP. Our speech coder shows 15.5 MIPS in performance which enables 4 channel CS-ACELP to be processed with one DSP16210.

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