• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1846-1856
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• 2016

This study proposes a novel feature point initialization method in order to improve the accuracy of feature point positions by fusing a vision sensor and a lidar. The initialization is a process that determines three dimensional positions of feature points through two dimensional image data, which has a direct influence on performance of a 6-DoF bearing-only SLAM. Prior to the initialization, an extrinsic calibration method which estimates rotational and translational relationships between a vision sensor and lidar using multiple calibration tools was employed, then the feature point initialization method based on the estimated extrinsic calibration parameters was presented. In this process, in order to improve performance of the accuracy of the initialized feature points, an iterative automatic scaling parameter tuning technique was presented. The validity of the proposed feature point initialization method was verified in a 6-DoF bearing-only SLAM framework through an indoor and outdoor tests that compare estimation performance with the previous initialization method.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.8
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• pp.804-809
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• 2007

Initialization problem is defined for indoor mobile robot as a whole process from arrival to normal operation in a new environment. The unstructured environment make the process much more difficult compared to industrial robot in structured environments. We propose a simple and efficient initialization process based on artificial stars on ceiling. Important task points and paths connecting task points are defined based on the corresponding artificial stars. This approach can be used for all kinds of indoor mobile robots with landmarks used for indoor localization.

• Smart Media Journal
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• v.11 no.11
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• pp.84-91
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• 2022

Baseboard Management Controller(BMC) supports server monitoring, maintenance, and control functions using various communication interfaces. However, if an unexpected problem occurs during the device driver initialization process, the BMC may not operate normally. Therefore, a boot process profiling tool that accurately analyzes the device driver initialization process and provides a function to check the analysis result is essential. Existing boot process profiling tools do not specifically provide the device driver initialization process and results required for BMC boot process analysis, forcing developers to use a combination of tools to analyze the boot process in detail. In this paper, we propose an integrated profiling tool for BMC's booting process. The proposed tool provides device driver initialization process analysis, CPU and memory usage analysis, and kernel version management functions. Users can easily analyze the booting process using the proposed tool, and the analysis result can be used to shorten the booting time. Also, the proposed tool is implemented in Linux-based BMC, and it is shown that the proposed tool is more efficient than the existing profiling tool.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.568-571
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• 2008

The computation of moving interface by the level set method typically requires reinitializations 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, accurate and robust reinitialization process is essential to the free-surface flows. In the present paper, we pursue further development of the reinitialization process, which evaluates directly level set function ${\phi}$ using a normal vector in the interface without solving the re-distancing equation of hyperbolic type. The Taylor-Galerkin approximation and P1P1splitting FEM are adopted to discretize advection equation of the level set function and the Navier-Stokes equation, respectively. Advection equation of free surface and re-initialization process are validated with benchmark problems, i.e., a broken dam flow and time-reversed single vortex flow. The simulation results are in good agreement with the existing results.

• 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 Environmental Science International
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• v.8 no.5
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• pp.611-616
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• 1999

The diagnostic software for the wastewater treatment plant using activated-sluge process is developed in order to increase the efficiency of management of the wastewater treatment plant. This software is based on the expert system and the visualized user interface, including the diagnosis of quantitative and qualitative data. For the generalization of this software, the initialization of each unit process and updating the files can be possible.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.216-219
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• 2008

It is necessary to study encryption for protection and safe transmission of the important information. Specially, the security in satellite data is also getting more and more important. This paper introduces DES and TDES algorithm, studies how to apply to satellite data with those algorithms and process of encryption and decryption for satellite data. Proposed encryption process in this paper will be utilized in satellite data for encryption in many satellites.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.47-50
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• 2022

In this paper, we proposed a method for Video-based point cloud compression reference software TMC2 encoder with an option for empty partitions in point cloud encoding. This encoder option allows tile initialization and process for an empty partition. The proposed method provides the TMC2 encoder the robustness to process dynamic point clouds.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1659-1664
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• 2011

Fuzzy C-Means (FCM) is one of the most widely used clustering algorithms and has been used in many applications successfully. However, FCM has some shortcomings and initial prototype selection is one of them. As FCM is only guaranteed to converge on a local optimum, different initial prototype results in different clustering. Therefore, much care should be given to the selection of initial prototype. In this paper, a new initialization method for FCM using kernel density estimation (KDE) is proposed to resolve the initialization problem. KDE can be used to estimate non-parametric data distribution and is useful in estimating local density. After KDE, in the proposed method, one initial point is placed at the most dense region and the density of that region is reduced. By iterating the process, initial prototype can be obtained. The initial prototype such obtained showed better result than the randomly selected one commonly used in FCM, which was demonstrated by experimental results.