• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.746-756
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• 2013

The emitter geolocation method using the time difference of arrival (TDOA) and the frequency difference of arrival (FDOA) has more accurate performance comparing to the single TDOA or FDOA based method. The estimation performance varies with the sensor paring strategies, the deployment and velocities of the sensors. Therefore, to establish effective strategy on the electronic warfare system, it is required to analyze the relation between the estimation accuracy and the operational condition of sensors. However, in the conventional non-iterative method, the restriction of the deployment of sensors and the reference sensor exists. Therefore, we derive the emitter geolocation method based on a Gauss-Newton method which is available to apply to any various sensor pairs and the deployment and velocities of the sensors. In addition, simulation results are included to compare the performance of geolocation method according to the used measurements: the combined TDOA/FDOA, TDOA, and FDOA. Also, we present that the combined TDOA/FDOA method outperforms over single TDOA or FDOA on the estimation accuracy with the CEP plane.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.549-559
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• 1997

A multiply-connected network unsteady flow model for the main reach of the Han River is developed. It is a variable parameter model which allows variable roughness coefficient for each computational point according to the spatial position and the value of discharge. Sensitivities of the model to roughness coefficient and weir-flow discharge coefficient are tested, and as a result Manning's roughness coefficient is selected as the calibration parameter. The model is calibrated and verified using the records of the past flood events. A modified Gauss-Newton method is used for the optimal calibration of roughness coefficients. From the calibration of variable parameter model, spatial variation and discharge dependence of Manning's roughness coefficient are identified. That is, the roughness coefficient is higher for the upstream reach of the Wangsook stream Junction, and it decreases as the discharge increases. It turns out through the verification that the stages calculated by the variable parameter model agree better with the observed than those by the conventional single parameter model. Spatial variation of the roughness coefficient appears to be more significant than the dependence of the discharge.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.161-166
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• 2002

Low-tension cables have been increasingly used in recent years due to deep-sea developments and the advent of synthetic cables. In the case of low-tension cables, large displacements may happen due to relatively small restoring forces of tension and thus the effects of fluid and geometric non-linearities become predominant. In this study, three-dimensional (3-D) dynamic behavior of a towed low-tension cable with non-uniform characteristics is numerically analyzed by considering fluid and geometric non-linearities and bending stiffness. A Fortran program is developed by employing a finite difference method. In the algorithm, an implicit time integration and Newton-Raphson iteration are adopted. For the calculation of huge size of matrices, block tri-diagonal matrix method is applied, which is much faster than the well-known Gauss-Jordan method in two point boundary value problems. Some case studies are carried out and the results of numerical simulations are compared with a in-house program of WHOI Cable with good agreements.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.312-319
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• 2007

The solution of the power flow is one of the most important problems in electrical power systems. These traditional methods such as Gauss-Seidel method and Newton-Raphson (NR) method have had drawbacks up to now such as initial values, abnormal operating solutions and divergences in heavy loads. In order to overcome theses problems, the power flow solution incorporating genetic algorithm (GA) is introduced in this paper. General operator of genetic algorithm, arithmetic crossover, and non-uniform mutation operator of GA are suggested to solve the power flow problem. While abnormal solution cannot be obtained by a NR method, multiple power flow solution can be obtained by a GA method. With a heavy load, both normal solution and abnormal solution can be obtained by a proposed method. In this paper, a floating number representation instead of the binary number representation is introduced for accuracy. Simulation results have been compared with traditional methods.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1145-1148
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• 2003

We show the mixed finite element method which induces solutions that has the same order of errors for both the gradient of the solution and the solution itself. The technique to construct an efficient reusable matrix is suggested. Two families of mixed finite element methods are introduced with an automatic generating technique for matrix with my order of basis. The generated matrix by this technique has more accurate values and is a sparse matrix. This new technique is applied to solve a minimal surface problem.

• ETRI Journal
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• v.32 no.6
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• pp.901-910
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• 2010

As a supplement to X-ray mammography, microwave imaging is a new and promising technique for breast cancer detection. Through solving the nonlinear inverse scattering problem, microwave tomography (MT) creates images from measured signals using antennas. In this paper, we describe a developed MT system and an iterative Gauss-Newton algorithm. At each iteration, this algorithm determines the updated values by solving the set of normal equations using Tikhonov regularization. Some examples of successful image reconstruction are presented.

• Water Engineering Research
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• v.2 no.3
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• pp.161-169
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• 2001

Present study deals with the development of a numerical model for the estimation of net annual recharge by coupling the Galerkin's finite element flow simulationl model with the Gauss-Newton-Marquardt optimization technique. The developed coupled numerical model is applied for estimating net annual recharge for Mahi Right Bank Canal (MRBC) project the norms of Groundwater Resources Estimation committee (1984, 1997) and Indian Agricultural research Institute(1983). It is observed that the estimated net recharge by inverse modeling is closer to the net recharge estimated using the water balance approach. Further it is observed that the computed head distribution from the estimated recharge agree closely with the observed head distribution. The study concludes that the developed model for inverse modeling can be successfully applied to large groundwater system involving regional aquifers where reliable recharge estimation always requires considerable time and financial resources.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1266-1272
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• 2014

We define the mobile robot navigation problem as an optimization problem to minimize the cost function with the pose error between the goal position and the position of a mobile robot. Using Gauss-Newton method for the optimization, the optimal speeds of the left and right wheels can be found as the solution of the optimization problem. Especially, the rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot using the Jacobian derived from the kinematic model. When the robot detects the obstacle using sensors, the sub-goal switching method is adopted for the efficient obstacle avoidance during the navigation. The performance was evaluated using the simulation and the simulation results show the validity of the proposed method.

• Journal of Korea Multimedia Society
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• v.16 no.11
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• pp.1338-1347
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• 2013

Face recognition is a science of automatically identifying individuals based their unique facial features. In order to avoid overfitting and reduce the computational reduce the computational burden, a new face recognition algorithm using PCA-fisher linear discriminant (PCA-FLD) and fuzzy radial basis function neural network (RBFNN) is proposed in this paper. First, face features are extracted by the principal component analysis (PCA) method. Then, the extracted features are further processed by the Fisher's linear discriminant technique to acquire lower-dimensional discriminant patterns, the processed features will be considered as the input of the fuzzy RBFNN. As a widely applied algorithm in fuzzy RBF neural network, BP learning algorithm has the low rate of convergence, therefore, an improved learning algorithm based on Levenberg-Marquart (L-M) for fuzzy RBF neural network is introduced in this paper, which combined the Gradient Descent algorithm with the Gauss-Newton algorithm. Experimental results on the ORL face database demonstrate that the proposed algorithm has satisfactory performance and high recognition rate.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.43-45
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• 2000

Traditionally, load flows have been calculated using the Gauss-Seidel and Newton-Raphson Method. DistFlow Method which is proposed by Wu and Baran is superior to the other two methods because it does not require the admittance matrix calculation to optimize the distribution system. This paper introduces a new alternative algorithm to the DistFlow Method which is slow and complex to find solutions as the number of lateral and sublateral increases. The proposed load flow method can construct System Jacobian easily. We can minimize the off-diagonal elements of the branch Jacobian and submatrices in the System Jacobian. Simulation results show that progressive performances of the proposed algorithm.