• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.109-116
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• 2010

This study is intended to propose a technique that can trace objects by utilizing the multimarker method in the Marker Recognition which is a bridge way connecting virtuality and reality in complex environments or in a condition hands become obstacles. In the existing marker method, the object becomes blinking when the maker is blocked since this method relies only on single marker. However, the researcher was able to confirm the appearance of augmented object when the marker was blocked for the multiple markers replaced the blocked one. In order to implement such technique, multi-marker estimation was utilized with perspective matrix. The advantage is the fast estimation process for there is no need of other calculation. The implemented technique can detect markers and locate their positions, represent 3-D object in various circumstances.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.875-882
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• 2010

Nowadays, the global market requires a variety of products and shorter life cycle to fulfill the diverse demands of customers. To survive in the turbulent and competitive markets, automobile assembly companies must design and implement manufacturing systems that respond rapidly to market demands. In this paper, methods for reconfiguring system based on modular concept is proposed using AR(Augmented reality) technologies. First, the relationship matrixes between change drivers and system components are generated to divide existing manufacturing system to each module. And, new change drivers are selected based on required function in new system. Through the modification of relationship matrix, the concept design of new system is proposed and implemented in AR environment. Finally, according to proposed methods and procedure in this paper, the existing cockpit assembly system is reconfigured to spare tire assembly system as a case study. As the use of the modular-based reconfiguration method in AR environment, the time and cost for reconfiguring manufacturing system will be reduced dramatically.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.806-811
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• 2017

This paper considers the delay-dependent stability of linear systems with a time-varying delay in the frame work of Lyapunov-Krasovskii functional(LKF) approach. In this approach, an integral inequality is essential to estimate the upper bound of time-derivative of LKF, and a less conservative one is needed to get a less conservative stability result. In this paper, based on free weighting matrices, an improved integral inequality encompassing well-known results is proposed and then a stability result in the form of linear matrix inequality is derived based on an augmented LKF. Finally, two well-known numerical examples are given to demonstrate the usefulness of the proposed result.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.399-406
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• 2000

We propose an nonlinear demodulation algorithm for undersampled multicomponent AM(Amplitude Modulation), FM(Frequency Modulation) and AM-FM signals. First, we derive respectively undersampling frequency of the AM, FM and AM-FM using undersampling scheme, and separate respectively monocomponent signals from multicomponent signals using periodic algebraic separation algorithm. In this case augmented separation matrix is very regular and sparse, it has a special structure. The proposed demodulation algorithm detects respectively message signals of the IA(Instantaneous Amplitude) and IF(Instantaneous Frequency) from descrete monocomponent AM, FM and AM-FM signals with an undersampling frequency to be controllable. Verifying the RMS(Root Mean Squares) errors of the detected signals, we show that the performance is excellent.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.11
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• pp.577-584
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• 2002

This paper presents a novel approach based on eigenvalue perturbation of augmented matrix(AMEP) to estimate the eigenvalue for variation of controller parameter. AMEP is a useful tool in the analysis and design of large scale power systems containing many different types of exciters, governors and stabilizers. Also, it can be used to find possible sources of instability and to determine the most sensitivity parameters for low frequency oscillation modes. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. Simulation results for interarea and local mode show that the proposed AMEP algorithm can be used for turning controller parameter, and verifying system data and linear model.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.112-115
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• 2001

Eigenvalue perturbation theory of augmented system matrix(AMEP) is a useful tool in the analysis and design of large scale power systems. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. AMEP for interarea and local mode can be used for turning controller parameter, and verifying system data and linear model of controller.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.265-274
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• 2016

In this paper, we consider a diffusion risk process, in which, its surplus process behaves like a Brownian motion in-between adjacent epochs of claims. We assume that the claims occur following a Poisson process and their sizes are independent and exponentially distributed with the same intensity. Our main goal is to derive the exact formula of the joint moment generating function of the ruin time and the total amount of aggregated claim sizes until ruin in the diffusion risk process. We also provide a method for computing the related first and second moments using the joint moment generating function and the augmented matrix exponential function.

• Journal of Mechanical Science and Technology
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• v.16 no.2
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• pp.203-210
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• 2002

For effective response surface modeling during sequential approximate optimization (SAO), the normalized and the augmented D-optimality criteria are presented. The normalized D-optimality criterion uses the normalized Fisher information matrix by its diagonal terms in order to obtain a balance among the linear-order and higher-order terms. Then, it is augmented to directly include other experimental designs or the pre-sampled designs. This augmentation enables the trust region managed sequential approximate optimization to directly use the pre-sampled designs in the overlapped trust regions in constructing the new response surface models. In order to show the effectiveness of the normalized and the augmented D-optimality criteria, following two comparisons are performed. First, the information surface of the normalized D-optimal design is compared with those of the original D-optimal design. Second, a trust-region managed sequential approximate optimizer having three D-optimal designs is developed and three design problems are solved. These comparisons show that the normalized D-optimal design gives more rotatable designs than the original D-optimal design, and the augmented D-optimal design can reduce the number of analyses by 30% - 40% than the original D-optimal design.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.560-570
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• 1999

This paper formulates the suboptimal robust Kalman filtering problem into two coupled Linear Matrix Inequality (LMI) problems by applying Lyapunov theory to the augmented system which is composed of the state equation in the uncertain linear system and the estimation error dynamics. This formulations not only provide the sufficient conditions for the existence of the desired filter, but also construct the suboptimal robust Kalman filter. The proposed filter can guarantee the optimized upper bound of the estimation error variance for uncertain systems with parametric uncertainties in both the state and measurement matrices. In addition, this paper shows how the problem of finding the minimizing solution subject to Quadratic Matrix Inequality (QMI), which cannot be easily transformed into LMI using the usual Schur complement formula, can be successfully modified into a generic LMI problem.

• Journal of the Korea Computer Graphics Society
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• v.3 no.2
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• pp.35-43
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• 1997

In monitor-based AR(Augmented Reality) systems, it is required to know the position and direction of a camera in order to combine real images from a camera with virtual images exactly_ Because a tracker is parted from a camera, however, there is a registration error caused by the inconsistency of a tracker with a camera. In this paper, we describe the error correction method using genetic algorithm. This method looks for the position and direction of a camera using genetic algorithm and solves the error correction matrix of it. And then it is registered of the real images and the revised virtual image. It has an effect on the error correction caused by the misalignment of a tracker with a camera in complex AR systems.