• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.660-662
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• 2000

The most important problem in traget tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters based on the dynamic equations. In this paper, we propose the extended robust Kalman filter(ERKF) which can be applied to the real target tracking system with the parameter uncertainties. To solve the robust nonlinear fettering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter(EKF) via 3-dimensional target example.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.553-561
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• 2018

To easily understand and systematically express the behaviors of the industrial systems, various system modeling techniques have been developed. Particularly, the importance of system modeling has been greatly emphasized in recent years since modern industrial systems have become larger and more complex. Multilevel flow modeling (MFM) is one of the qualitative modeling techniques, applied for the representation and reasoning of target system characteristics and phenomena. MFM can be applied to industrial systems without additional domain-specific assumptions or detailed knowledge, and qualitative reasoning regarding event causes and consequences can be conducted with high speed and fidelity. However, current MFM techniques have a limitation, i.e., the dynamic features of a target system are not considered because time-related concepts are not involved. The applicability of MFM has been restricted since time-related information is essential for the modeling of dynamic systems. Specifically, the results from the reasoning processes include relatively less information because they did not utilize time-related data. In this article, the concepts of time-to-detect and time-to-effect were adopted from the system failure model to incorporate time-related issues into MFM, and a methodology for enhancing MFM-based reasoning with time-series data was suggested.

• Earthquakes and Structures
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• v.18 no.1
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• pp.45-56
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• 2020

The application of critical excitation method with displacement-based objective function for multi degree of freedom (MDOF) systems is investigated. To this end, a new critical excitation method is developed to find the critical input motion of a MDOF system as a synthetic accelerogram. The upper bound of earthquake input energy per unit mass is considered as a new constraint for the problem, and its advantages are discussed. Considering this constraint, the critical excitation method is then used to generate synthetic accelerograms for MDOF models corresponding to three shear buildings of 10, 16, and 22 stories. In order to demonstrate the reliability of generated accelerograms to estimate dynamic response of the structures, three target ground motions with considerable level of energy contents are selected to represent "real critical excitation" of each model, and the method is used to re-generate these ground motions. Afterwards, linear dynamic analyses are conducted using these accelerograms along with the generated critical excitations, to investigate the key parameters of response including maximum displacement, maximum interstory drift, and maximum absolute acceleration of stories. The results show that the generated critical excitations can make an acceptable estimate of the structural behavior compared to the target ground motions. Therefore, the method can be reliably implemented to generate critical excitation of the structure when real one is not available.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.95-108
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• 2010

In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.

• International Journal of Automotive Technology
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• v.3 no.4
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• pp.165-170
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• 2002

For a vehicle Anti-lock Braking System (ABS), the control target is to maintain friction coefficients within maximum range to ensure minimum stopping distance and vehicle stability. But in order to achieve a directionally stable maneuver, tire side forces must be considered along with the braking friction. Focusing on combined braking and turning operation conditions, this paper presents a new control scheme for an ABS controller design, which calculates optimal target wheel slip ratio on-line based on vehicle dynamic states and prevailing road condition. A fuzzy logic approach is applied to maintain the optimal target slip ratio so that the best compromise between braking deceleration, stopping distance and direction stability performances can be obtained for the vehicle. The scheme is implemented using an 8-DOF nonlinear vehicle model and simulation tests were carried out in different conditions. The simulation results show that the proposed scheme is robust and effective. Compared with a fixed-slip ratio scheme, the stopping distance can be decreased with satisfactory directional control performance meanwhile.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.53-62
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• 2023

Effects-Based Operations (EBO) refers to a process for achieving strategic goals by focusing on effects rather than attrition-based destruction. For a successful implementation of EBO, identifying key nodes in an adversary network is crucial in the process of EBO. In this study, we suggest a network-based approach that combines network centrality and optimization to select the most influential nodes. First, we analyze the adversary's network structure to identify the node influence using degree and betweenness centrality. Degree centrality refers to the extent of direct links of a node to other nodes, and betweenness centrality refers to the extent to which a node lies between the paths connecting other nodes of a network together. Based on the centrality results, we then suggest an optimization model in which we minimize the sum of the main effects of the adversary by identifying the most influential nodes under the dynamic nature of the adversary network structure. Our results show that key node identification based on our optimization model outperforms simple centrality-based node identification in terms of decreasing the entire network value. We expect that these results can provide insight not only to military field for selecting key targets, but also to other multidisciplinary areas in identifying key nodes when they are interacting to each other in a network.

• Earthquakes and Structures
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• v.15 no.5
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• pp.529-540
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• 2018

The influences of initial damage paths and aftershock (AS) spectral shape on the assessment of AS collapse fragility are investigated. To do this, a four-story ductile reinforced concrete (RC) frame structure is employed as the study case. The far-field earthquake records recommended by FEMA P695 are used as AS ground motions. The AS incremental dynamic analyses are performed for the damaged structure. To examine the effect of initial damage paths, a total of six kinds of initial damage paths are adopted to simulate different initial damage states of the structure by pushover analysis and dynamic analysis. For the pushover-based initial damage paths, the structure is "pushed" using either uniform or triangle lateral load pattern to a specified damage state quantified by the maximum inter-story drift ratio. Among the dynamic initial damage paths, one single mainshock ground motion or a suite of mainshock ground motions are used in the incremental dynamic analyses to generate a specified initial damage state to the structure. The results show that the structure collapse capacity is reduced as the increase of initial damage, and the initial damage paths show a significant effect on the calculated collapse capacities of the damaged structure (especially at severe damage states). To account for the effect of AS spectral shape, the AS collapse fragility can be adjusted at different target values of ${\varepsilon}$ by using the linear correlation model between the collapse capacity (in term of spectral intensity) and the AS ${\varepsilon}$ values, and coefficients of this linear model is found to be associated with the initial damage states.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.24-31
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• 2014

The modern version of aircrafts is allowed to guarantee the superior handing qualities within the entire flight envelope by imposing the adequate stability and flying qualities on a target aircraft through the various techniques of flight control law design. Generally, the flight control law of the aircraft in service applies the various techniques of the verified control algorithm, such as dynamic inversion and eigenstructure assignment. The supersonic trainer employs the RSS(Relaxed Static Stability) concept in order to improve the aerodynamic performance in longitudinal axis and the longitudinal control laws employ the dynamic inversion with proportional-plus-integral control method. And, lateral-directional control laws employ the blended roll system of both beta-betadot feedback and simple roll rate feedback with proportional control method in order to guarantee aircraft stability. In this paper, the lateral-directional flight control law is designed by applying dynamic inversion control technique as a different method from the current supersonic trainer control technique, where the roll rate command system is designed at the lateral axis for the rapid response characteristics, and the sideslip command system is adopted at the directional axis for stability augmentation. The dynamic inversion of a simple 1st order model is applied. And this designed flight control law is confirmed to satisfy the requirement presented from the military specification. This study is expected to contribute to design the flight control law of KF-X(Korean Fighter eXperimental) which will proceed into the full-scale development in the near future.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.785-790
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• 2006

In RFID-based SCM, The traceability and product information is the important target data. In this paper, efficient items traceability model and the integrated model of the product between RFID network and GDS(Global Data Synchronization) network are studied. Information consists of the dynamic data generated from RFID network and static data generated from GDS Network. The integrated model will provide the interoperability between 2 kinds of networks.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.83-84
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• 2013

최근 다양한 시스템의 상태를 추정하는데 시스템의 운동 특성을 모델링하는 기법이 많이 연구되고 있다. 이 기법은 시스템의 운동 특성을 수학적으로 모델링하는 것으로 모델링의 정확도에 따라 시스템의 상태 추정 정확도에 많은 영향을 미치게 된다. 따라서 본 논문에서는 표적의 기동 특성을 모델링하고 표적의 현재와 과거의 상태를 이용하여 정의된 기동 모델 중 적합성을 판단하는 기법을 제시하며 시뮬레이션을 통하여 기동하는 표적의 모델을 정확하게 판단하는지를 검증하고자 한다.