• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.165-170
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• 2013

When we build up a 3D model from the given 2D images, linear algorithms are often used to reduce computational cost or for initialization of nonlinear algorithms. However, contemporary linear algorithms have apparently linear structures, but virtually they are implemented using SVD. The SVD is also implemented using numerical analysis algorithms that need initialization. Moreover, solutions using SVD are more difficult to analyze than closed-form solutions. To avoid from such inconvenient numerical analysis algorithms of the contemporary methods and for convenient analysis of solutions, this paper proposes a convenient linear method that produces a closed-form solution.

• Journal of Ocean Engineering and Technology
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• v.17 no.3 s.52
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• pp.13-20
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• 2003

This research aims at investigation of accuracy potential of RTK(Real-Time Kinematic) GPS in combination with Echo Sounder(E/S) for the coastal mapping. Apart from this purpose, the accuracy of ambiguity resolution with the OTF(On The Fly) method was tested with respect to the initialization time. The result shows that the accuracy is better than 1cm with 5-minute initialization in the distance of 10km baseline. The seaside topography was measured by the RTK GPS only, on the other hand the seafloor topography was surveyed in combination of RTK GPS and E/S. Comparing to the volume of seaside measured by RTK GPS and digital topographical map, the difference of only $2\%$ was achieved. This indicates that the coastal mapping. As a result, it has been revealed that every possible noise in surveying could be corrected and the accuracy could be improved. The accuracy of GPS data acquired in real time was as good as that acquired by post processing. It is expected that it will be useful for the analysis of coastal geographic characteristics because DTM(Digital Terrain Model) can be also constructed for the harbor reclamation, the dredging, and the variation of soil movement in a river.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.10
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• pp.754-760
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• 2008

Computation of moving interface by the level set method typically requires the reinitialization of level set function. An inaccurate estimation of level set function $\phi$ results in incorrect free-surface capturing and thus errors such as mass gain/loss. Therefore, an accurate and robust reinitialization process is essential to the simulation of free-surface flows. In the present paper, we pursue further development of the reinitialization process, which evaluates level set function directly using a normal vector on the interface without solving there-distancing equation of hyperbolic type. The Taylor-Galerkin approximation and P1P1 splitting/SUPG (Streamline Upwind Petrov-Galerkin) FEM are adopted to discretize advection equation of the level set function and the incompressible Navier-Stokes equation, respectively. Advection equation and re-initialization process of free surface capturing are validated with benchmark problems, i.e., a broken dam flow and timereversed single vortex flow. The simulation results are in good agreement with the existing results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.42-48
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• 1990

In this paper robust test generation for stuck-open faults in CMOS circuits is proposed. By obtaining initialization patterns and test patterns using the relationship of bit position and Hamming weight among input vectors for CMOS circuit test generation time for stuck-open faults can be reduced, and the problem of input transition skew which make fault detection difficult is solved, and the number of test sequences are minimized. Also the number of test sequences is reduced by arranging test sequences using Hamming distance between initialization patterns and test patterns for circuit.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1702-1708
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• 2007

Dragon Stream Cipher is proposed for software base implementation in the eSTREAM project. Now this stream cipher is selected as a phase 3 focus candidate. Dragon is a new stream cipher contructed using a single word based NIFSR(non-linear feed back shift register) and 128/256 key/IV(Initialization Vector). Dragon is the keystream generator that produce 64bits of keystream. In this paper, we present an implementation of Drag(m stream cipher algorithm in hardware. Finally, the implementation is on Altera FPGA device, EP3C35F672I and the timing simulation is done on Altera's Quartus II. A result of 111MHz maximum clock rate and 7.1Gbps is throughput is obtained from the implementation.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.121-129
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• 2021

This paper deals with a super-resolution that improves the resolution of side scan sonar images using learning-based compressive sensing. Learning-based compressive sensing combined with deep learning and compressive sensing takes a structure of a feed-forward network and parameters are set automatically through learning. In particular, we propose a method that can effectively extract additional information required in the super-resolution process through various initialization methods. Representative experimental results show that the proposed method provides improved performance in terms of Peak Signal-to-Noise Ratio (PSNR) and Structure Similarity Index Measure (SSIM) than conventional methods.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.853-858
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• 1995

The initial condition of a core transient should be consistent with real core state for the simulation of the core tansient. The initial xenon distribution, which can not be measured in the core, has a significant effect on the transient with xenon dynamics. In the simulation of the transient starting from non-equilibrium xenon state, the accurate initialization of the non-equilibrium xenon distribution is essential for the prediction of the core transient behavior. In this study, a xenon initialization method to predict the core transient more accurately was developed through the equivalent pre-xenon-oscillation which represents the tenon oscillation before the transient and verified by the application of the simulation for a startup test of Yonggwang Unit 3.

• Journal of IKEEE
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• v.27 no.4
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• pp.430-438
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• 2023

The Modular Multilevel Converter (MMC) has emerged as a key component in HVDC systems due to its ability to efficiently transmit large amounts of power over long distances. In such systems, accurate estimation of the MMC capacitor voltage is of utmost importance for ensuring optimal system performance, stability, and reliability. Traditional methods for voltage estimation may face limitations in accuracy and robustness, prompting the need for innovative approaches. In this paper, we propose a novel distributed neural network observer specifically designed for MMC capacitor voltage estimation. Our observer harnesses the power of a multi-layer neural network architecture, which enables the observer to learn and adapt to the complex dynamics of the MMC system. By utilizing a distributed approach, we deploy multiple observers, each with its own set of neural network layers, to collectively estimate the capacitor voltage. This distributed configuration enhances the accuracy and robustness of the voltage estimation process. A crucial aspect of our observer's performance lies in the meticulous initialization of random weights within the neural network. This initialization process ensures that the observer starts with a solid foundation for efficient learning and accurate voltage estimation. The observer iteratively updates its weights based on the observed voltage and current values, continuously improving its estimation accuracy over time. The validity of proposed algorithm is verified by the result of estimated voltage at each observer in capacitor of MMC.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.469-479
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• 2014

N-RTK(Network based RTK) methods are able to improve the accuracy of GNSS positioning results through modelling of the distance-dependent error sources(i.e. primarily the ionospheric and tropospheric delays and orbit errors). In this study, the comparison of the TTFF(Time-To-Fix-First ambiguity), accuracy and discrepancies in horizontal/vertical components of N-RTK methods(VRS and FKP) with the static GNSS at 20 Unified Control Stations covering Incheon metropolitan city area during solar storms(Solar cycle 24 period) were performed. The results showed that the best method, compared with the statics GNSS survey, is the VRS, followed by the FKP, but vertical components of both VRS and FKP were approximately two times bigger than horizontal components. The reason for this is considered as the ionospheric scintillation because of irregularities in electron density, and the tropospheric scintillation because of fluctuations on the refractive index take the place. When the TTFF at each station for each technique used, VRS gave shorter initialization time than FKP. The possible reasons for this result might be the inherent differences in principles, errors in characteristics of different correction networks, interpolating errors of FKP parameters according to the non-linear variation of the dispersive and non-dispersive errors at rover when considering both domestic mobile communication infra and the standardized high-compact data format for N-RTK. Also, those test results revealed degradation of positing accuracy, long initialization time, and sudden re-initialization, but more failures to resolve ambiguity during space weather events caused by Sunspot activity and solar flares.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.141-149
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• 2005

Tn general. Gaussian mixture model (GMM) is used to estimate the speaker model from the speech for speaker identification. The parameter estimates of the GMM are obtained by using the Expectation-Maximization (EM) algorithm for the maximum likelihood (ML) estimation. However the EM algorithm has such drawbacks that it depends heavily on the initialization and it needs the number of mixtures to be known. In this paper, to solve the above problems of the EM algorithm. we propose an EM algorithm with the initialization based on incremental ${\cal}k-means$ for GMM. The proposed method dynamically increases the number of mixtures one by one until finding the optimum number of mixtures. Whenever adding one mixture, we calculate the mutual relationship between it and one of other mixtures respectively. Finally. based on these mutual relationships. we can estimate the optimal number of mixtures which are statistically independent. The effectiveness of the proposed method is shown by the experiment for artificial data. Also. we performed the speaker identification by applying the proposed method comparing with other approaches.