• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.292-295
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• 2008

We propose a PON repeater system which transports multiple PON channels at the same time over the physical limit of the standard E-PON reach. To increase the physical reach up to 60km, we used the O-E-O (optic-electric-optic) signal regeneration on an active remote terminal which is placed between a central office and passive remote nodes. Also, by incorporating the well-established WDM technology to aggregate multiple E-PON channels, we successfully increased the split ratio (the number of subscribers per fiber core) to over 256.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2142-2148
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• 2009

A microgrid is defined as two or more distributed generation or storage assets configured in a networks and capable of operation in parallel or independently form a larger electric gird, while providing continuous power to one or more end users. And when microgrid are separated from grid oprating protection devices by faults of the grid side, microsources should charge electrical power needs of loads in microgrid and operate maintaining power quality. The magnitude of the switching transients will vary based on voltage phase difference between microgrid and grid, when the microgrid is resynchronized to grid. In this paper, when microgrid is resynchronized to grid, we analyzed the existing problems for reducing switching transients of SS(Static Switch).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1351-1359
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• 2007

In this paper, we have studied the power quality(PQ) diagnosis system with the two methods for PQ diagnosis. One to Apply a regulation value in compliance with mathematics calculation, and the other Automatic identification using Neural network algorithm. Neural network algorithm is used for an automatic diagnosis of the PQ. The regulation proposed by IEEE 1159 Working group is applied for the precision of the diagnosis. In order to divide accurate segmentation, the algorithm for a computer training used the back propagation out of several neural network algorithms. We have configured the proto-type sample by using Labview and a programmed Neural Networks Algorithm using with C. And arbitrary electric Signal generated by OMICRON Company's CMC 256-6 for an efficiency test.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.122-124
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• 1995

Electrical transmission and distribution networks must withstand an occasionally abnormal condition such as a fault, with prejudicial consequences for the line, transformers or generators. And the improvement of reliability and quality of the delivered power from an electric utility motivates the development of new technologies in power applications. As a part of these studies, the usefulness and utility of a superconduction fault current limiter(SFCL) are shown. The SFCL is applied to 22.9KV three-phase power system and performed short circuit studies. The verified quench characteristic of SFCL is adopted for fault simulation and the results are compared with those of system which have not SFCL.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.231-233
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• 2015

무선 센서 네트워크는 다수의 센서 노드와 하나의 싱크노드로 구성된다. 센서 네트워크상에 분포된 센서 노드들은 데이터 전송 중에 배터리 재충전이나 변경이 곤란하다. 센서들의 제한적 특성을 때문에 일반 유선 네트워크와 달리 에너지 효율적인 네트워크 설계를 요구한다. 이러한 문제를 해결하기 위해 계층적 클러스터 라우팅 프로토콜로서 LEACH 프로토콜을 분석하고, 센서들의 에너지 소모를 줄이고, 네트워크 수명을 연장하는 개선된 LEACH 라우팅 프로토콜을 제안한다. 최적 클러스터를 결정하는 기법을 이용하여 클러스터 수를 고려한 클러스터를 형성하고, 성능 분석은 MATALAB을 이용하여 시뮬레이션 하였으며, 본 개선된 프로토콜이 LEACH 프로토콜과 비교하여 우수함을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.879-881
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• 2019

전자의무기록 (EMR)과 같은 의료 현장에서 수집되는 대용량의 데이터는 임상 해석적으로 잠재가치가 크고 활용도가 다양하나 결측값이 많아 희소성이 크다는 한계점이 있어 분석이 어렵다. 특히 EMR의 정보수집과정에서 발생하는 결측값은 무작위적이고 임의적이어서 분석 정확도를 낮추고 예측 모델의 성능을 저하시키는 주된 요인으로 작용하기 때문에, 결측치 대체는 필수불가결하다. 최근 통상적으로 활용되어지던 통계기반 알고리즘기반의 결측치 대체 알고리즘보다는 딥러닝 기술을 활용한 알고리즘들이 새로이 등장하고 있다. 본 논문에서는 Generative Adversarial Network를 기반한 최신 결측값 대치 알고리즘인 Generative Adversarial Imputation Nets을 적용하여 EMR에서의 성능을 분석해보고자 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.720-722
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• 2009

Optimal operation of electric power generating plants is very essential for any power utility organization to reduce input costs and possibly the prices of electricity in general. This paper developed models for load forecasting using neural networks approach. This model is tested using actual load data of the Busan and weather data to predict the load of the Busan for one month in advance. The test results showed that the neural network forecasting approach is more suitable and efficient for a forecasting application.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.118-134
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• 2021

In this study, we provide trends on alternative fuel vehicles promoted by postal agencies in 10 countries in North America, the EU, and Asia. It describes the specifications of most EV vehicles in operation, plans, and strategies to replace existing internal combustion engines with new vehicles in the future and provides the current status of alternative vehicle charging networks in each postal agency. This paper will help postal agencies, logistics companies, automobile companies, motorcycle companies, and even individuals who want to use vehicles with alternative fuels, such as electric vehicles, on strategies to establish and implement before introducing and operating the vehicles.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.88-92
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• 2023

Lithium-ion batteries are actively used in various industrial sites such as field robots, drones, and electric vehicles due to their high energy efficiency, light weight, long life span, and low self-discharge rate. When using a lithium-ion battery in a field, it is important to accurately estimate the SoC (State of Charge) of batteries to prevent damage. In recent years, SoC estimation using data-based artificial neural networks has been in the spotlight, but it has been difficult to deploy in the embedded board environment at the actual site because the computation is heavy and complex. To solve this problem, neural network lightening technologies such as network pruning have recently attracted attention. When pruning a neural network, the performance varies depending on which layer and how much pruning is performed. In this paper, we introduce an optimized pruning technique by improving the existing pruning method, and perform a comparative experiment to analyze the results.