• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.553-563
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• 1994

This paper presents a filtering method using neural networks to extract fundamental frequency components of the transient wave signals in power systems. Based on the ability of multilayer feedforward neural networks to approximate any continuous function, a neural networks mapping filter is proposed for the protective distance relaying systems to extract the effective components efficiently. A characteristic feature of this mapping filter is composed of the multilayer perceptron neural networks which are trained by using random signals and those are mapped to the DFT filtering computational structure by GDR(Generalized Delta Rule). The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1204-1206
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• 2005

This paper deals with magnetic field analysis and computation of cogging torque in IPM motor with an analytical method, which is based on the Conformal Mapping technique. The magnetic field is analyzed by solving space harmonic field analysis due to inserted PM magnetizing distribution. Conformal Mapping method is then used for considering the slot opening effect and rotor saliency effect on the air-gap field magnetic distribution. Then, by integrating the field over the stator surface, cogging torque is calculated. The validity of the proposed analytical method is confirmed by comparing the results with 2-D FEA results.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.1
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• pp.69-77
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• 2021

The widely used low-cost design methodology for IoT devices is very popular. In such a networked device, memory is composed of flash memory, SRAM, DRAM, etc., and because it processes a large amount of data, memory design is an important factor for system performance. Therefore, each device selects optimized design factors such as function, performance and cost according to market demand. The design of a memory architecture available for low-cost IoT devices is very limited with the configuration of SRAM, flash memory, and DRAM. In order to process as much data as possible in the same space, an architecture that supports parallel processing units is usually provided. Such parallel architecture is a design method that provides high performance at low cost. However, it needs precise software techniques for instruction and data mapping on the parallel architecture. This paper proposes an instruction/data mapping method to support optimized parallel processing performance. The proposed method optimizes system performance by actively using hardware and software parallelism.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.259-272
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• 2023

In this paper, we suggest a new method for the prediction of sharp changes in particulate matter (PM₁₀) using quantile mapping. To predict the current PM₁₀ density in Seoul, we consider PM₁₀ and precipitation in Baengnyeong and Ganghwa monitoring stations observed a few hours before. For the PM₁₀ distribution estimation, we use the extreme value mixture model, which is a combination of conventional probability distributions and the generalized Pareto distribution. Furthermore, we also consider a quantile generalized additive model (QGAM) for the relationship modeling between precipitation and PM₁₀. To prove the validity of our proposed model, we conducted a simulation study and showed that the proposed method gives lower mean absolute differences. Real data analysis shows that the proposed method could give a more accurate prediction when there are sharp changes in PM₁₀ in Seoul.

• The Journal of Korea Robotics Society
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• v.18 no.2
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• pp.135-142
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• 2023

Light detection and ranging (LiDAR) sensors have been most widely used in terrestrial robotic applications because they can provide dense and precise measurements of the surrounding environments. However, the reliability of LiDAR measurements can considerably vary due to the different reflectivities of laser beams to the reflecting surface materials. This study presents a robust LiDAR-based mapping method for the varying laser reflectivities in indoor environments using the framework of simultaneous localization and mapping (SLAM). The proposed method can minimize the performance degradations in the SLAM accuracy by checking and discarding potentially unreliable LiDAR measurements in the SLAM front-end process. The gaps in point-cloud maps created by the proposed approach are filled by a Gaussian process regression method. Experimental results with a mobile robot platform in an indoor environment are presented to validate the effectiveness of the proposed methodology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.270-275
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• 2018

Method for improving the image quality are divided into a tone mapping method and a retinex theory based method. Typical example of the image quality enhancement method using tone mapping method is one using image characteristics like histogram. In this paper, we propose a hardware design of real-time wide dynamic range algorithm based on tone mapping method for image quality enhancement. The proposed method divides the image into the luminance and chroma components and then improves the chroma region based on the variation of the luminance component. Adding to that, it is designed to be compatible with the existing 8-bit signal, using high quality image with 12-bit extended signal according to the desired flow. As a result of simulation, it is confirmed that the image quality is improved, and the hardware design is confirmed that the real-time operations is possible at the maximum frequency at 138.26MHz.

• ETRI Journal
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• v.36 no.1
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• pp.134-140
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• 2014

Many reports have shown that the access pattern for geospatial tiles follows Zipf's law and that its parameter ${\alpha}$ represents the access characteristics. However, visits to geospatial tiles have temporal and spatial popularities, and the ${\alpha}$-value changes as they change. We construct a mathematical model to simulate the user's access behavior by studying the attributes of frequently visited tile objects to determine parameter estimation algorithms. Because the least squares (LS) method in common use cannot obtain an exact ${\alpha}$-value and does not provide a suitable fit to data for frequently visited tiles, we present a new approach, which uses a moment method of estimation to obtain the value of ${\alpha}$ when ${\alpha}$ is close to 1. When ${\alpha}$ is further away from 1, the method uses the associated cache hit ratio for tile access and uses an LS method based on a critical cache size to estimate the value of ${\alpha}$. The decrease in the estimation error is presented and discussed in the section on experiment results. This new method, which provides a more accurate estimate of ${\alpha}$ than earlier methods, promises more effective prediction of requests for frequently accessed tiles for better caching and load balancing.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.787-790
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• 1998

In this paper, we presents a method for multi-level logic mainmization which is suitable for the minimization of look-up table type FPGAs. A pattern extraction algorithm is minimized AND/XOR multi-level circuits. The circuits apply to Roth-Karp decomposition which is most commonly used technique in the FPGA technology mapping. We tested the FPGA synthesis method using pattern extraction on a set of benchmark. The proposed method achieved reductions on the number of LUTs in mapping soultion as compared with MISII(or SIS) or previous results〔5〕

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.46-54
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• 2006

The design method of synthetic aperture radar processor (SARP) in the critical design stage is to describe the processing algorithm, to estimate the fractional errors, and to set out the software (SW) and hardware (HW) mapping. The previous design methods for SARP are complex and depend on HW. Therefore, this paper proposes a critical design method that is of more general and independent of HW. This methodology can be applied for developing the space-based SARP using range-Doppler algorithm (RDA).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.4
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• pp.213-220
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• 2017

This study examines the limitations of existing crime mapping that relies mainly on reported crime data, suggests a crime mapping method based on experts' and users' assessments of a neighborhood environment as an alternative approach, and conducts a case study on a real-world site by applying the suggested approach. According to the results of the case analysis, while the areas adjoining arterial roads with heavy pedestrian traffic were shown as high crime risk areas in the crime map based on actual reported crime data, the areas adjoining local roads with low pedestrian traffic were high-risk areas in the crime risk area map based on experts' and residents' evaluations. This study makes a contribution to the field in that it demonstrates the detailed application process of crime risk area mapping according experts' and residents' evaluations, compares the results with those of an existing crime map, and finally shows that the former can function as a complement to the latter.