• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.245-252
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• 2020

It is very important to evaluate on/off-line stability to operate the power system stably and economically. Until now, we have continuously secured the operation reliability of the power system through the evaluation of transient, voltage and small signal stability. This paper proposes that it is possible to operate in KWAMS by applying the multi-section analysis and subspace methods and verifying the reliability of the algorithms to directly estimate the dominant oscillation mode of the power system from the signal waveform acquired from the phasor measurement units. In addition, this paper shows that the dominant oscillation mode can be detected from real-time measurement data in power systems. Therefore, if we can monitor the state of the power system in real time, it is possible to avoid a large-scale power outage by knowing the possibility of the power system accident in advance.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.77-87
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• 2019

One of important concerns in information security is to control information flow. It is whether to protect confidential information from being leaked, or to protect trusted information from being tainted. In this paper, we present Piosk (Physical blockage of Information flow Kiosk) that addresses both the problems practically. Piosk can forestall and prevent the leakage of information, and defend inner tangible assets against a variety of malwares as well. When a visitor who carries a re-writable portable storage device, must insert the device into Piosk installed next to the security gate. Then, Piosk scans the device at the very moment, and detects & repairs malicious codes that might be exist. After that, Piosk writes the contents (including sanitized ones) on a new read-only portable device such as a compact disk. By doing so, the leakage of internal information through both insiders and outsiders can be prevented physically. We have designed and prototyped Piosk. The experimental verification of the Piosk prototype implementation reveals that, Piosk can accurately detect every malware at the same detection level as Virus Total and effectively prevent the leakage of internal information. In addition, we compare Piosk with the state-of-the-art methods and describe the special advantages of Piosk over existing methods.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.9-19
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• 2019

Service and users over the Internet are increasing rapidly. Cyber attacks are also increasing. As a result, information leakage and financial damage are occurring. Government, public agencies, and companies are using security systems that use signature-based detection rules to respond to known malicious codes. However, it takes a long time to generate and validate signature-based detection rules. In this paper, we propose and develop signature based detection rule generation and verification systems using the signature extraction scheme developed based on the LDA(latent Dirichlet allocation) algorithm and the traffic analysis technique. Experimental results show that detection rules are generated and verified much more quickly than before.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.55-61
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• 2018

본 연구는 시각 동기 위상 측정 정보를 이용하여 전력계통에 나타나는 여러 가지 동요 현상을 검출하기 위한 기초 연구로써, 시계열 데이터 분석 분야로 분류된다. 제시한 방법은 비선형 동특성에 해석 기반으로 접근하여 전력계통에 나타날 수 있는 여러 동요 현상을 범용적으로 검출해 낼 수 있다. 비선형 동요 현상의 신호적 패턴을 수학적으로 기본 순시치 파형으로부터 피크치 샘플링을 통해 전개하여 계통 요소간 간섭으로 인한 원하지 않는 진동 모드를 검출하고자 한다. 계통의 변화로 진동 모드가 나타날 때, 2차원 평면에 실효치로 환산한 시계열 전압 데이터와 선형화된 플로퀘트 상수(Floquet multiplier)를 맵핑하여 도시하고, 정상상태 지점으로부터 거리를 계산하여 최대 리아프노프 지수 계산을 통해 계통이 불안정하게 되는 시간을 시계열 데이터 분석으로 추정하는 것이 본 방법의 핵심이다. 이러한 접근으로 제시한 비선형 동요 검출 알고리즘을 적용하여 디지털 필터 적용 또는 주파수 영역 해석과 같은 오프라인 Study와 달리 온라인으로 신속하게 계통의 현재 상태를 알 수 있게 된다.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.17-24
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• 2019

In this paper, we analyzed the effect of power system load model on the short-term voltage stability analysis results. First, we introduced common load models. We also confirmed that some load models can not represent actual system phenomena even if the model parameters are optimized. Also, we studied about the influences of load parameters and regional characteristics of load model on the sort-term voltage stability of KEPCO power system considering the contingency. The results showed that the importance of selecting a load model was confirmed again. And we recognized about it can be understood that it should reflect the load characteristics of the area near the assumed contingency more accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4105-4121
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• 2021

Recently, malware classification based on Deep Neural Networks (DNN) has gained significant attention due to the rise in popularity of artificial intelligence (AI). DNN-based malware classifiers are a novel solution to combat never-before-seen malware families because this approach is able to classify malwares based on structural characteristics rather than requiring particular signatures like traditional malware classifiers. However, these DNN-based classifiers have been found to lack robustness against malwares that are carefully crafted to evade detection. These specially crafted pieces of malware are referred to as adversarial examples. We consider a clever adversary who has a thorough knowledge of DNN-based malware classifiers and will exploit it to generate a crafty malware to fool DNN-based classifiers. In this paper, we propose a DNN-based malware classifier that becomes resilient to these kinds of attacks by exploiting Generative Adversarial Network (GAN) based data augmentation. The experimental results show that the proposed scheme classifies malware, including AEs, with a false positive rate (FPR) of 3.0% and a balanced accuracy of 70.16%. These are respective 26.1% and 18.5% enhancements when compared to a traditional DNN-based classifier that does not exploit GAN.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.21-27
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• 2022

The rotorcraft engine gearbox transmits the power generated by the turboshaft engine to the rotor by reducing the rotational speed and increasing the torque. The core of the rotorcraft engine gearbox is lightweight performance, which requires maximum weight reduction within the range that meets various requirements and constraints. Therefore, lightweight design through gear macro geometry optimization is necessary. In this study, gear macro geometry optimization was performed to reduce the weight of a rotorcraft engine gearbox. NSGA-III was used for the optimization, resulting in a combination of the gear ratio and macro geometry that minimizes the weight of the total gear. In addition, the safety factor of the gears satisfied the given conditions.

• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.57-66
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• 2013

The needs for reusable 3D visualization tool has been being raised in various industries. Especially in the defense modeling and simulation (M&S) domain, there are abundant researches about reusable and interoperable visualization system, since it has a critical role to the efficient decision making by offering diverse validation and analyzing processes. To facilitate the effectiveness, states-of-the-arts M&S systems are applying VR (Virtual Reality) or AR (Augmented Reality) technologies. To reduce the work burden authors design a collaborative visualization environment based on a commercial game engine Unity3D. We define the requirements of the warfare simulation by analyzing pros and cons of existing tools and engines such as SIMDIS or Vega, and apply functionalities of the commercial game engine to satisfy the requirements. A prototype has been implemented as the collaborative visualization environment of iCAVE at KAIST, which is a facility for immersive virtual environment. The facility is intraoperative with smart devices.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1171-1179
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• 2014

ISO(Independent System Operator) or TSO(Transmission System Operator) use power system analysis program to simulate contingency analysis and remedial actions to operate power system stably. Generally, power system analysis program provides automated analysis functions(or modules) to deal with wide area power system. However, because of missed contingency cases, automated contingency analysis has no practical use or has limitation. And in case of remedial action, it doesn't support automated function or takes a lot of times to study, because of simulation in manual for each cases. This paper suggests that new relation with buses and transmission line properties of power system DB used for power system analysis program to simulate automated contingency including all contingency cases needed in the field without missed cases. And it proposes automated remedial action scheme based on practical approach analysis to alleviate overloading or voltage problems. Finally it deals with automated contingency/remedial action analysis(automated scheduled outage) program which is developed by KEPCO and its performance and proposed schemes are proven by case study for real Korean power system data.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.199-207
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• 2018

This study aims to analyze Next Production Revolution (NPR) technologies through evidence-based keyword network in order to cope with the change of production paradigm called the Fourth Industrial Revolution (4IR). For the analysis, a total of 441 papers related to NPR or 4IR were extracted and the NPR technology network was constructed based on the simultaneous appearance relationship of the author keywords of these papers. Based on the NPR technology network, we explored key technologies through analysis of centrality and keyword group. As a result, technologies such as 'digital twin' and 'modeling and simulation', discovering insights by connecting the virtual and physical world in real time and reflecting them into design and process, are analyzed as key technologies.