• ETRI Journal
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• 제41권5호
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• pp.585-598
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• 2019

A cyber-physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well-funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game-theoretical model considering both low- and high-interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.

• 대한전기학회논문지:전력기술부문A
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• 제48권6호
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• pp.704-711
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• 1999

This paper presents a design of fuzzy power system stabilizer (FPSS) using adaptive evolutionary computation (AEC). We have proposed an adaptive evolutionary algorithm which uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. FPSS shows better control performances than conventional power system stabilizer (CPSS) in three-phase fault with heavy load which is used when tuning FPSS. To show the robustness of the proposed FPSS, it is appliedto damp the low frequency oscillations caused by disturbances such as three-phase fault with normal and light load, the angle deviation of generator with normal and light load and the angle deviation of generator with heavy load. Proposed FPSS shows better robustness than CPSS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1177-1179
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• 1999

This paper presents a design of artificial neural network power system stabilizer(ANNPSS) using adaptive evolutionary algorithm(AEA). We have proposed an adaptive evolutionary algorithm which uses both a genetic algorithm(GA) and an evolution strategy(ES), useing the merits of two different evolutionary computations. ANNPSS shows better control performances than conventional power system stabilizer(CPSS) in three-phase fault with heavy load which is used when tuning ANNPSS. To show the robustness of the proposed ANNPSS, it is applied to damp the low frequency oscillation caused by disturbances such as three-phase fault with normal and light load. the proposed ANNPSS shows better robustness than CPSS.

• 대기
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• 제21권4호
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• pp.391-404
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• 2011

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.

• 영재교육연구
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• 제26권4호
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• pp.677-697
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• 2016

본 연구에서는 창의적 산출물 평가의 대표적 도구인 O'Quin과 Besemer(1989)의 '창의적 산출물 분석행렬(CPAM)'과 '창의적 산출물 어의 척도(CPSS)'의 두 가지의 산출물 평정 척도를 적용하여 동일한 산출물을 평가하는 데 있어 평가 결과의 차이를 분석하였다. 연구 결과, 창의적 산출물 평가에서 평가자의 암묵적 지식은 존재하며, 암묵적 지식과 명시적 지식에 기반한 평가의 평정결과는 차이가 있는 것으로 나타났다. 평가자에게 명시적 지식이 쌓여 갈수록 산출물에 대한 전반적인 평가 점수는 낮게 나타나 더 엄격해지는 경향을 보였다. 상대적으로 세분화된 채점기준을 가진 CPSS로 평정하였을 때는 창의성의 하위 차원에서 점수가 모두 낮게 나타났으며, 평가자가 산출물에 대한 첫인상이나 개인적 평가 기준이 너무 확고한 경우에는 평정도구에 영향을 받지 않을 수도 있다는 것을 살펴볼 수 있었다. 영재교육 담당교사들은 창의적 산출물 평가에서 전문가들과 유사한 평가를 하고 있었으며 산출물 평가 도구를 사전에 충분히 숙지하고 산출물을 지도하거나 평가한다면 보다 새롭고, 유용하고 적절하며, 해결성이 높은 창의적인 산출물이 생성 될 수 있을 것이다.

• ETRI Journal
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• 제40권4호
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• pp.421-434
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• 2018

The application of deep neural networks (DNNs) to connect the world with cyber physical systems (CPSs) has attracted much attention. However, DNNs require a large amount of memory and computational cost, which hinders their use in the relatively low-end smart devices that are widely used in CPSs. In this paper, we aim to determine whether DNNs can be efficiently deployed and operated in low-end smart devices. To do this, we develop a method to reduce the memory requirement of DNNs and increase the inference speed, while maintaining the performance (for example, accuracy) close to the original level. The parameters of DNNs are decomposed using a hybrid of canonical polyadic-singular value decomposition, approximated using a tensor power method, and fine-tuned by performing iterative one-shot hybrid fine-tuning to recover from a decreased accuracy. In this study, we evaluate our method on frequently used networks. We also present results from extensive experiments on the effects of several fine-tuning methods, the importance of iterative fine-tuning, and decomposition techniques. We demonstrate the effectiveness of the proposed method by deploying compressed networks in smartphones.

• KIEE International Transactions on Power Engineering
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• 제3A권4호
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• pp.181-190
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• 2003

This paper presents the design of a fuzzy power system stabilizer (FPSS) using an adaptive evolutionary algorithm (AEA). AEA consists of genetic algorithm (GA) for a global search capability and evolution strategy (ES) for a local search in an adaptive manner when the present generation evolves into the next generation. AEA is used to optimize the membership functions and scaling factors of the FPSS. To evaluate the usefulness of the FPSS, we applied it to a single-machine infinite bus system (SIBS) and a power system simulator at the Korea Electrotechnology Research Institute. The FPSS displays better control performance than the conventional power system stabilizer (CPSS) for a three-phase fault in heavy load, which is used when tuning FPSS. To show the robustness of the FPSS, it is applied with disturbances such as change of mechanical torque and three-phase fault in nominal and heavy load, etc. The FPSS also demonstrates better robustness than the CPSS. Experimental results indicate that the FPSS has good system damping under various disturbances such as one-line to ground faults, line parameter changes, transformer tap changes, etc.

• 한국융합학회논문지
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• 제3권4호
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• pp.23-28
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• 2012

이 연구는 1990년대부터 국내외 전반에 걸쳐 진행된 다양한 규모와 기관에서 진행된 급성 뇌졸중 환자의 연구를 바탕으로 뇌졸중 환자의 예후 관련 접근에 대해 올바른 발전 방향을 모색하고자 한다. 이를 위하여 국내외 문헌 검토는 BNBI PubMed, KMBase, RISS, KoreaMed를 이용하였다. 검색된 논문을 대상으로 발생빈도, 병원 전 뇌졸중 환자의 평가 및 응급처치, 병원 내 전문치료로 구분하여 분석하였다. 뇌졸중 평가의 중요한 척도로 사용되고 있는 신시내티 뇌졸중 척도와 로스앤젤레스 뇌졸중 척도를 이용한 평가가 중요하며, 이를 바탕으로 전문적인 응급처치가 시행되어야 한다.

• 정보과학회 논문지
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• 제45권1호
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• pp.36-44
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• 2018

4차 산업혁명의 도래로 인하여 자율주행 자동차, 지능 로봇 등을 구현을 위한 ICT 분야의 기술 개발이 시급히 요구되고 있다. 특히 융합 IT를 기반으로 하는 모든 시스템들이 센서나 액추에이터와 연동하는 CPS(Cyber Physical Systems) 형태로 개발되고 있다. 기존의 CPS 명세는 단일 시스템의 행위만을 명세하였기 때문에, 초연결성과 초융합성을 갖는 4차 산업혁명 시대의 CPS 시스템이 갖는 협업 및 다양성 측면에 명세는 충분히 제시되지 못하였다. 특히 실시간적 특성을 갖는 다양한 응용에서는 더욱 협업적 특성을 고려한 행위 모델링이 이루어지지 못하였다. 본 논문에서는 이러한 실시간 협업 환경에서 임무를 수행하는 CPS용 임베디드 소프트웨어를 개발할 때, 어떠한 비기능 요구사항이 식별되어야 하는가를 정의한다. 이러한 요구사항은 ISO 25010 표준에 근거하여 도출하며, 실시간 협업을 위해 상태 기반의 Timed Process를 이용하여 정형적으로 명세한다. 도출된 비기능 요구사항들은 추후 CPS 기반의 새로운 임베디드 소프트웨어에 대한 요구사항을 정의하기 위해 재사용될 수 있을 것이며, 이를 통해 CPS의 품질만족도를 향상시킬 수 있을 것이다.

• Biomolecules & Therapeutics
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• 제18권3호
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• pp.271-279
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• 2010

Streptococcus pneumoniae is the major pathogen that frequently causes serious infections in children, the elderly and immunocompromised patients. S. pneumoniae is known to produce reactive oxygen species (ROS) and S. pneumoniae-produced ROS is considered to play a role in pneumococci pathogenesis. SIGN-R1 is the principal receptor of capsular polysaccharides (CPSs) of S. pneumoniae. However, there is a considerable lack of knowledge about the protective role of SIGN-R1 against S. pneumoniae-produced ROS in SIGN-$R1^+$ macrophages. While investigating the protective role of SIGN-R1 against ROS, we found that SIGN-R1 intimately bound to peroxiredoxin-1 (Prx-1), one of small antioxidant proteins in vitro and in vivo. This interaction was increased with ROS generation which was produced by stimulating SIGN-R1 with dextran, a polysaccharide ligand of SIGN-R1. Also, SIGN-R1 crosslinking with 22D1 anti-SIGN-R1 antibody increased Prx-1 in vitro or in vivo. These results suggested that SIGN-R1 stimulation with CPSs of S. pneumoniae increase the expression level of Prx-1 through ROS and its subsequent interaction to SIGN-R1, providing an important antioxidant role for the host protection against S. pneumoniae.