• 디지털산업정보학회논문지
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• 제9권1호
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• pp.1-7
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• 2013

The cloud computing is technology which gives flexible and solid infrastructure to IT environment. With this technology multiple computing environment can be consolidated in to a single server so that maximize system resource utilization. Better processing power can be achieved with less system resource. IT manager can cope with increasing unnecessary cost for additional server and management cost as well. This means a enterprise is able to provide services with better quality and create new services with surplus resource. The time required for recovery from system failure will be reduced from days to minutes. Enhanced availability and continuity of enterprise business minimize the codt and the risk produced by service discontinuity. In this paper, we propose framework architecture that is strong against denial-of-service attack.

• 대한전기학회논문지:전력기술부문A
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• 제49권3호
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• pp.95-106
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• 2000

The load frequency control of power system is one of important subjects in view of system operation and control. That is even though the rapid load disturbances were applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow one on each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation were given, the unstable phenomenal of power system can be often brought out because of the large frequency deviation and the unsuppressible power line one. Therefore, it is desirable to design the robust neuro-fuzzy controller which can stabilize effectively the given power system as soon as possible. In this paper the robust neuro-fuzzy controller was proposed and applied to control of load frequency over multi-area power system. The architecture and algorithm of a designed NFC(Neuro-Fuzzy Controller) were consist of fuzzy controller and neural network for auto tuning of fuzzy controller. The adaptively learned antecedent and consequent parameters of membership functions in fuzzy controller were acquired from the steepest gradient method for error-back propagation algorithm. The performances of the resultant NFC, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the load frequency control of multi-area power system, when the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbances of internal parameters and external stepwise load stepwise load changes, the superiorities of the proposed NFC in robustness and adaptive rapidity to the conventional controllers were proved.

• 한국정보전자통신기술학회논문지
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• 제6권4호
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• pp.243-248
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• 2013

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 한국건축시공학회지
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• 제13권2호
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• pp.159-168
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• 2013

Construction projects have become increasingly complex in recent years, resulting in substantial safety hazards and frequent fall accidents. In an attempt to prevent fall accidents, various safety management systems have been developed. These systems have mainly been evaluated qualitatively and subjectively by practitioners or supervisors, and there are few tools that can be used to quantitatively evaluate the performance of safety management systems. We propose an expertise-based safety performance evaluation model (EXSPEM), which integrates a fuzzy approach-based analytic hierarchy process and a regression approach. The proposed model uses S-shaped curves to represent the degree of contribution by subjective expertise and is verified by a genetic algorithm. To illustrate its practical application, EXSPEM was applied to evaluate the safety performance of a newly developed real-time mobile detector monitoring system. It is expected that this model will be a helpful tool for systematically evaluating the application of a robust safety control and management system in a complex construction environment.

• 설비공학논문집
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• 제16권11호
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• pp.1068-1076
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• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• Smart Structures and Systems
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• 제30권3호
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Journal of Astronomy and Space Sciences
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• 제41권1호
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• pp.43-60
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• 2024

Korea Pathfinder Lunar Orbiter (KPLO) is South Korea's first space exploration mission, developed by the Korea Aerospace Research Institute. It aims to develop technologies for lunar exploration, explore lunar science, and test new technologies. KPLO was launched on August 5, 2022, by a Falcon-9 launch vehicle from cape canaveral space force station (CCSFS) in the United States and placed on a ballistic lunar transfer (BLT) trajectory. A total of four trajectory correction maneuvers were performed during the approximately 4.5-month trans-lunar cruise phase to reach the Moon. Starting with the first lunar orbit insertion (LOI) maneuver on December 16, the spacecraft performed a total of three maneuvers before arriving at the lunar mission orbit, at an altitude of 100 kilometers, on December 27, 2022. After entering lunar orbit, the commissioning phase validated the operation of the mission mode, in which the payload is oriented toward the center of the Moon. After completing about one month of commissioning, normal mission operations began, and each payload successfully performed its planned mission. All of the spacecraft operations that KPLO performs from launch to normal operations were designed through the system operations design process. This includes operations that are automatically initiated post-separation from the launch vehicle, as well as those in lunar transfer orbit and lunar mission orbit. Key operational procedures such as the spacecraft's initial checkout, trajectory correction maneuvers, LOI, and commissioning were developed during the early operation preparation phase. These procedures were executed effectively during both the early and normal operation phases. The successful execution of these operations confirms the robust verification of the system operation.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2388-2398
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• 2017

In this study, we propose a robust face recognition system to pose variations based on automatic pose estimation. Radial basis function neural network is applied as one of the functional components of the overall face recognition system. The proposed system consists of preprocessing and recognition modules to provide a solution to pose variation and high-dimensional pattern recognition problems. In the preprocessing part, principal component analysis (PCA) and 2-dimensional 2-directional PCA ($(2D)^2$ PCA) are applied. These functional modules are useful in reducing dimensionality of the feature space. The proposed RBFNNs architecture consists of three functional modules such as condition, conclusion and inference phase realized in terms of fuzzy "if-then" rules. In the condition phase of fuzzy rules, the input space is partitioned with the use of fuzzy clustering realized by the Fuzzy C-Means (FCM) algorithm. In conclusion phase of rules, the connections (weights) are realized through four types of polynomials such as constant, linear, quadratic and modified quadratic. The coefficients of the RBFNNs model are obtained by fuzzy inference method constituting the inference phase of fuzzy rules. The essential design parameters (such as the number of nodes, and fuzzification coefficient) of the networks are optimized with the aid of Particle Swarm Optimization (PSO). Experimental results completed on standard face database -Honda/UCSD, Cambridge Head pose, and IC&CI databases demonstrate the effectiveness and efficiency of face recognition system compared with other studies.

• 대한전자공학회논문지TC
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• 제45권12호
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• pp.74-82
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• 2008

본 논문에서는 다중 체인구조를 이용한 P2P 기반 IPTV 시스템을 제안한다. 제안하는 시스템은 P2P 네트워크의 특징인 peer의 빈번한 가입과 탈퇴 상황에서 단순한 과정으로 네트워크를 재구성하는 장점이 있다. 인터넷과는 달리 ISP가 관리하는 IPTV 환경은 전송회선의 속도와 안정성이 일정수준으로 보장되어 있다. 따라서 IPTV 환경에서의 P2P 네트워크는 단순성 측면을 우선적으로 고려해야 한다. 기존에 제안되어있는 단일 체인구조는 단순성을 강조하였으나 같은 채널을 시청하는 peer의 개수가 증가하면 체인의 끝 부분에 연결되어 있는 peer는 상당한 delay가 발생한다. 제안하는 시스템은 이러한 delay 문제를 해결하기 위하여 체인을 여러 개의 레벨로 분리하고 각 레벨은 다시 span으로 나누었다. 레벨과 span으로 분리를 하였지만 기본적인 구조는 체인구조이므로 peer가 join 하거나 departure 할 경우에 단순한 네트워크의 재구성 과정을 제공한다. 수치적인 해석을 통해 본 논문에서 제안한 다중 체인구조를 이용한 P2P 시스템이 단일 체인구조 방식에 비해 delay 및 신뢰도 성능이 우수하다는 것을 보여준다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3870-3884
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• 2020

The proposed framework of Four Layer Robust Storage in Cloud (FLRSC) architecture involves host server, local host and edge devices in addition to Virtual Machine Monitoring (VMM). The goal is to protect the privacy of stored data at edge devices. The computational intelligence (CI) part of our algorithm distributes blocks of data to three different layers by partially encoded and forwarded for decoding to the next layer using hash and greed Solomon algorithms. VMM monitoring uses snapshot algorithm to detect intrusion. The proposed system is compared with Tiang Wang method to validate efficiency of data transfer with security. Hence, security is proven against the indexed efficiency. It is an important study to integrate communication between local host software and nearer edge devices through different channels by verifying snapshot using lamport mechanism to ensure integrity and security at software level thereby reducing the latency. It also provides thorough knowledge and understanding about data communication at software level with VMM. The performance evaluation and feasibility study of security in FLRSC against three-layered approach is proven over 2³² blocks of data with 98% accuracy. Practical implications and contributions to the growing knowledge base are highlighted along with directions for further research.