• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.35-48
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• 2008

In this paper, we propose a Dynamic Heuristic to reduce the number of node accesses and improve quality of path in the client-based navigation service. The Dynamic Heuristic is to use heuristic data from server that is calculated with traffic data. The server-based navigation service provides a path searched on server and transmits it to client, but we propose that server only provide heuristic data to client. The proposed client searches a path with heuristic transmitted data from server. We present a new algorithm for using Dynamic Heuristic in the path-finding. The algorithm bases Grid Based Path-Finding, and has minimum speed data of edges in grid. It removes several grids whose minimum speed is less than limited speed.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.75-80
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• 2012

In this paper, a new energy harvesting technology using stray electric field of an electric power line is presented. It is found that energy can be harvested and stored in the storage capacitor that is connected to a cylindrical aluminum foil wrapped around a commercial insulated 220 V power line. The average current flowing into 47 ${\mu}F$ storage capacitor is about 4.53 ${\mu}A$ with 60 cm long cylindrical aluminum foil, and it is possible to operate wireless sensor node to transmit RF data every 42 seconds. The harvested average power is about 47 ${\mu}W$ in this case. Since the energy can be harvested without removing insulating sheath, it is believed that the proposed harvesting technology can be applied to power the sensor nodes in wireless ubiquitous sensor network and smart grid system.

• Archives of design research
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• v.13 no.3
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• pp.29-38
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• 2000

Human has been living in the relation with diverse artifacts ranging from simple tools to complex systems. The relation is an interaction between user and product with input and output process to achieve a certain goals. Natural inter-connection is very important to this interaction. The visualized operation and the dear feedback of product play a critical role in making input and output distinct at both sides. So product innovation means removing mental and physical loads between product and user based on understanding and analyzing interaction. This study proposes the interaction grid as a framework to visualize the interaction. The interaction grid is the format to describe the input and output process between user and product. Modeling and analysis of interaction is based on the interaction grid. Finally, this study discusses the idea exploration method for product innovation with interaction grid, and develops prototype of interaction analysis system for supporting idea exploration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.845-851
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• 2015

Load shedding is a last measure to avoid nationwide cascading collapses of power system by removing the pre-determined amount of loads from the main grid. In Korea, SPS(Special Protection System) is prepared to keep the power system stability from the extreme contingency of the critical transmission line losses. Among them, we need to pay attention to 765kV T/L’s because they have great influence on the total system stability. According to the present SPS operating guide, the total loads of 1,500MW should be removed through 2 step under-voltage load shedding(UVLS) scheme in case of 765kV T/L’s contingencies. However, it is not clear to defined how to determine the typical load reduction amounts for each case. This paper proposes a method to estimate appropriate amounts of load shed for 765kV T/L’s contingencies by analyzing the relevant national and international standards.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.41-45
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• 2019

In this paper, we propose the interference cancellation scheme of end-to-end method algorithm for power line communication (PLC) systems in smart grid. The proposed scheme estimates the channel noise information of receiver by applying a deep learning model at the receiver. Then, the estimated channel noise is updated in database. In the modulator, the channel noise which reduces the power line communication performance is effectively removed through interference cancellation technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the theoretical model based on additive white Gaussian noise. As a result, the proposed interference cancellation with deep learning improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC for smart grid and general communication systems.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.5
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• pp.372-375
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• 2021

A three-leg inverter-type isolated DC-DC Converter that can use 220 and 440 V grid input voltages is introduced. The secondary circuit structure of the proposed topology is center-tap, which is the same as the conventional phase-shifted full-bridge converter. However, the primary circuit structure is composed of a three-leg inverter structure and a transformer, in which two primary windings are connected in series. The proposed circuit structure has a wider input voltage range than the conventional phase-shifted full-bridge converter, and the circulating-current on the primary-side is reduced. In addition, the voltage stress at the secondary rectifier is greatly improved, and high efficiency can be achieved at a high input voltage by removing the snubber circuit added to the conventional converter. Prototype converters with input DC of 311 V, output of 622 V, and 50 V and 6 kW class specifications were designed and manufactured to verify the validity of the proposed topology; the experimental results are presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.29-33
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• 2022

In this paper, we propose the deep learning based pre interference cancellation scheme algorithm for power line communication (PLC) systems in smart grid. The proposed scheme estimates the channel noise information by applying a deep learning model at the transmitter. Then, the estimated channel noise is updated in database. In the modulator, the channel noise which reduces the power line communication performance is effectively removed through interference cancellation technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the theoretical model based on additive white Gaussian noise. As a result, the proposed interference cancellation with deep learning improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC for smart grid and general communication systems.

• Journal of the military operations research society of Korea
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• v.30 no.1
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• pp.30-47
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• 2004

This research considers a Network Diversion Problem (NDP) in the directed graph, which is to identify a minimum cost set of links to cut so that any communication paths from a designated source node to a destination node must include at least one link from a specified set of arcs which is called the diversion arcs. We identify a redundant constraint from an earlier formulation. The problem is known to be NP-hard, however a detailed proof has not been given. We provide the proof of the NP-hardness of this problem. We develop a tabu search algorithm that includes a preprocessing procedure with two steps for removing diversion arcs as well as reducing the problem size. Computational results of the algorithm on instances of general graphs and grid graphs are reported.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.126-129
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• 2005

Change detections is carried out under the assumption that pixel boundaries of geometrically corrected time series satellite images cover the same location. However that assumption can be wrong when shifts in the pointing direction of a satellite sensor occurs. Currently, although the influence of misregistration on landcover change detection has been investigated, there has been little research on the influence of pointing direction shifts of a satellite sensor. In this study, a simple method for reducing the effects of pointing direction shifts of a satellite sensor is proposed: the classification of two ASTER images was carried out using the linear spectral mixture analysis, the two classification results were resampled into a geometrically fixed grid, and then the change detection of the two ASTER images was carried out by comparing the resampled classification results of the two images. The proposed method showed high performance in discriminating between changed areas and unchanged areas by removing the pointing direction shifts of a satellite sensor.