• Information Systems Review
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• v.10 no.2
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• pp.269-289
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• 2008

It is very difficult problem to estimate and evaluate the performance of e-government system which scope and size are large and its effectiveness can not be seen shortly but reveals after several years. It is because the previous offline processes can not be transformed to online ones fully and shortly. For such e-transformation cases, the performance evaluation model should be adjusted and modified gradually as time passes. This paper propose new EEM(E-transformation Evaluation Model) model and methodology to evaluate G2B system that is one of large e-government project. EEM model can derive monetary value of e-transformatized business process areas(online areas). It also estimate the expected effect of offline area that is not yet transformed to online. EEM model consists of standard model, verification model and estimation model with some variables such as evaluation year, evaluation area and data type. By using survey data and database data together it can validate the correctness of the model and derive the effect of the system introduction. This paper also propose EEM evaluation methodology consisting of 5 stages and 10 sub processes to evaluate online and offline effect efficiently. To show the usefulness of this study, we evaluate the performance of Korea G2B system named KONEPS which is famous as a successful e-government case in the world by using the proposed model and methodology. The proposed model and methodology can be applied to different similar areas including e-government projects and large scale information system introduction in private sectors. This study can be also used for establishing appropriate policies about e-government project and informatization issues.

• Journal of the HCI Society of Korea
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• v.12 no.3
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• pp.25-33
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• 2017

Current video service market doesn't satisfy the users' needs who want to find new and interesting contents despite the vast amount of contents. Now it is continuously necessary to Study on technology and using experience is continuously required in online video service area to stimulate the watching motivation efficiently with such as recommendation or promotion. One of efficient ways of increasing the using motivation is to give the users pleasure when they use the services. This study focused on 'unexpected funny finding' as a strategy of providing pleasure of using. It was believed that it could increase the pleasure of using the service, if serendipity, which means unexpected pleasure, accidental finding such as finding a beautiful $caf{\acute{e}}$ or meeting a friend at a certain place unexpectedly, is applied. This study defines the serendipity as 'contents that give unexpected pleasure' at the online video environment. First it theoretically extracted the various characteristics of serendipity through reading many books. Next it verified the other concept of serendipity through the diary of users' survey to additionally extract the characteristics of serendipity at video environment that are hard to find in books. It formed estimation items for the characteristics of the extracted serendipity and tested them in youtube to confirm the characteristics of serendipity being found in video service and observe potential factors that make it. As a result if verified and confirmed four factors that cause serendipity at video environment. This study could be used as basic data to understand the concept of serendipity. It has an academic meaning in the point that it could be a useful reference for the future study that analyzes the role or effect of serendipity at IT area including online video service.

• Smart Structures and Systems
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• v.8 no.4
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• pp.367-384
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• 2011

This paper presents the design and experimental evaluation of fast output sampling feedback controller to minimize structural vibration of a cantilever beam using Shape Memory Alloy (SMA) wires as control actuators and piezoceramics as sensor and disturbance actuator. Linear dynamic models of the smart cantilever beam are obtained using online recursive least square parameter estimation. A digital control system that consists of $Simulink^{TM}$ modeling software and dSPACE DS1104 controller board is used for identification and control. The effectiveness of the controller is shown through simulation and experimentation by exciting the structure at resonance.

• Journal of Power Electronics
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• v.15 no.3
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• pp.786-795
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• 2015

In this paper, an active damping control scheme for LLCL filters based on the PR (proportional-resonant) regulator is proposed for grid-connected three-level T-type PWM converter systems. The PR controller gives an infinite gain at the resonance frequency. As a result, the oscillation can be suppressed at that frequency. In order to improve the stability of the system in the case of grid impedance variations, online grid impedance estimation is applied. Simulation and experimental results have verified the effectiveness of the proposed scheme for three-phase T-type AC/DC PWM converters.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.9
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• pp.32-39
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• 2006

In this paper, an iterative subspace-based calibration algorithm for a CDMA-based antenna array in the presence of unknown gain and phase error is presented. The algorithm does not depend on the array geometry and does not require a prior knowledge of the Directions Of Arrival (DOA) of the signals. The method requires the code sequence of a reference user only. The proposed algorithm is based on the subspace method and root finding approach, and it provides estimates of the calibration vector, the DOA and the channel impulse response, by using the code sequence of a reference user. The performance of the proposed algorithm was investigated by means of computer simulations and was verified using field data measured through a custom-built W-CDMA test-bed. The data show that experimental results match well with the theoretical calibration algorithm. Also, teh study propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the requirement of initial guessing in the subspace-based approach.

• Journal of Power Electronics
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• v.9 no.3
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• pp.377-385
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• 2009

In this paper, a diagnosis method for switch open-circuit faults in three-phase PWM inverters is proposed, which employs support vector machine (SVM) as classifying method. At first, a discrete wavelet transform (DWT) is used to detect a discontinuity of currents due to the fault, and then the features for fault diagnosis are extracted. Next, these features are employed as inputs for the SVM training. After training, the SVM produces an optimized boundary which is used identifying the fault. Finally, the fault classification is performed online with instantaneous features. The experimental results have verified the validity of the proposed estimation algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1617-1620
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• 2005

The current control for interior permanent magnet machines is more complicate than surface permanent magnet machine because of its torque characteristic depending on the reluctance. For high performance torque control, it requires state decoupling between the d-current and q-current dynamics. However the variation of the inductances, which couples the state dynamics of the currents, makes the state decoupling difficult. So some decoupling methods have developed to cope this variations and each current can be regulated independently. This paper presents a novel approach for fully decoupling the states cross-coupling using parameter adaptation. The adaptation method is based on the error between reference currents and the currents with state decoupling which have to follow the references. This method is more object-oriented than the other online parameter estimation methods in IPM machine and other electrical machines

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.965-974
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• 2003

In this paper we propose an incremental classification of multi-class data set by LS-SVM. By encoding the output variable in the training data set appropriately, we obtain a new specific output vectors for the training data sets. Then, online LS-SVM is applied on each newly encoded output vectors. Proposed method will enable the computation cost to be reduced and the training to be performed incrementally. With the incremental formulation of an inverse matrix, the current information and new input data are used for building another new inverse matrix for the estimation of the optimal bias and lagrange multipliers. Computational difficulties of large scale matrix inversion can be avoided. Performance of proposed method are shown via numerical studies and compared with artificial neural network.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.72-81
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• 2009

This paper presents a robust adaptive control method using model reference control strategy against autonomous robot systems with random friction nature. We approximate a nonlinear robot system model by means of a feedback linearization approach to derive nominal control law. We construct a Least Square (LS) based observer to estimate friction dynamics online and then represent a perturbed system model with respect to approximation error between an actual friction and its estimation. Model reference based control design is achieved to implement an auxiliary control in order for reducing control error in practice due to system perturbation. Additionally, we conduct theoretical study to demonstrate stability of the perturbed system model through Lyapunov theory. Numerical simulation is carried out for evaluating the proposed control methodology and demonstrating its superiority by comparing it to a traditional nominal control method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.11
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• pp.650-653
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• 2005

In this paper, adaptive high-order neural network controller(AHONNC) is adopted to control an induction servomotor. A algorithm is developed by combining compensation control and high-order neural networks. Moreover, an adaptive bound estimation algorithm was proposed to estimate the bound of approximation error. The weight of the high-order neural network can be online tuned in the sense of the Lyapunov stability theorem; thus, the stability of the closed-loop system can be guaranteed. Simulation results for induction servomotor drive system are shown to confirm the validity of the proposed controller.