• Journal of KIISE:Software and Applications
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• v.33 no.2
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• pp.167-185
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• 2006

Software architecture, which is the high level model of a software system, should be specified with ADLs (Architecture Description Languages) for its clarity and preciseness. Most of ADLs such as ACME, however, have not come into extensive use in industries since ADL users should learn a distinct notation specific to architecture. On the other hand, UML is a do facto standard general modeling language for software developments. UML provides a consistent notation and various supporting tools during the whole software development cycle. UML, being a general modeling language, does not provide all concepts that are important to architecture description. UML should be extended in order to precisely model architecture. A number of researches on architecture modeling based on WML have been progressed. Ail of them, however, are based on the UML1.x. UML2.0 embraces much more concepts that are important to architecture modeling than UML1.x. In this paper. we defined an architecture modeling language based on UML2.0. We defined Generic ADL by extending UML2.0 and applied the defined Generic ADL to a restaurant reservation system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.26-32
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• 2007

In sequential speaker classification, the lack of prior information about the speakers poses a challenge for model initialization. To address the challenge, a predetermined generic model set, called Sample Speaker Models, was previously proposed. This approach can be useful for accurate speaker modeling without requiring initial speaker data. However, an optimal method for sampling the models from a generic model pool is still required. To solve this problem, the Speaker Quantization method, motivated by vector quantization, is proposed. Experimental results showed that the new approach outperformed the random sampling approach with 25% relative improvement in error rate on switchboard telephone conversations.

• Wind and Structures
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• v.24 no.3
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• pp.223-247
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• 2017

By using numerical simulation, vast and detailed information and observation of the physics of flow over a train model can be obtained. However, the accuracy of the numerical results is questionable as it is affected by grid convergence error. This paper describes a systematic method of computational grid refinement for the Unsteady Reynolds Navier-Stokes (URANS) of flow around a generic model of trains using the OpenFOAM software. The sensitivity of the computed flow field on different mesh resolutions is investigated in this paper. This involves solutions on three different grid refinements, namely fine, medium, and coarse grids to investigate the effect of grid dependency. The level of grid independence is evaluated using a form of Richardson extrapolation and Grid Convergence Index (GCI). This is done by comparing the GCI results of various parameters between different levels of mesh resolutions. In this study, monotonic convergence criteria were achieved, indicating that the grid convergence error was progressively reduced. The fine grid resolution's GCI value was less than 1%. The results from a simulation of the finest grid resolution, which includes pressure coefficient, drag coefficient and flow visualization, are presented and compared to previous available data.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.10-19
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• 1996

In order to build a model to predict accidents in a complicated man-machine sytem, human errors and mechanical reliability can be viewed as the most important factors. Such factors are explicitly included in a generic model. Another point to keep in mind is that the model should be constructed so that the data in a type of accident can be utilized to predict other types of accidents. Based on such a generic prediction model, we analyze the effects of system reliability. When we improve the system reliability, in other words, when there are changes in model parameters, the predicted time to next accidents should be modified influencing the effects of system reliability improvements. We apply Bayesian approach and finds the formula to explain how a change on the machine reliability or human error probability influences the time to next accident.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1013-1014
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• 2008

In this paper, we propose a new method of generating 3D face by using single frontal face image and 3D generic face model. By using active appearance model (AAM), the control points among facial feature points were localized in the 2D input face image. Then, the transform parameters of 3D generic face model were found to minimize the error between the 2D control points and the corresponding 2D points projected from 3D facial model. Finally, by using the obtained model parameters, 3D face was generated. We applied this 3D face to 3D game framework and found that the proposed method could make a realistic 3D face of game user.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.113-116
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• 2000

Human face recognition and 3D human face reconstruction has been studied in this paper. To find the facial feature points, find edge from input image and analysis the accumulated histogram of edge information. This paper use a Generic Face Model to display the 3D human face model which was implement with OpenGL and generated with 500 polygons. For reality of 3D human face model, we propose Group matching mapping method between facial feature points and the one of Generic Face Model. The personalized 3D human face model which resembles real human face can be generated automatically in less than 5 seconds on Pentium PC.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.263-268
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• 2001

A new control scheme s proposed for the control of reactive batch distillation (RBD) column. A nonlinear wave model captures the essential dynamic behavior of the RBD process. The proposed control scheme is based on both Generic Model Control(GNC) and nonlinear wave model. The control scheme uses a profile position of the column as a controlled variable. Ethanol esterification process using RBD is chosen as an example process. Tight control of the distillate purity is obtained with the use of the proposed control scheme.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.673-675
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• 1995

A nonlinear process-model based control for main steam temperature control of a 100MW oil-fired drum-type fossil power plant is delveloped and its performances are compared to those of the conventional PID control. The process model for simulation is derived based "first priciple approach" and is validated in steady and transient conditions. The model is in good agreements with the field test data. Performances of the nonlinear PMBC for main steam temperature control are far superior to those of PID in all aspects for the disturbances of ramp increase in load and step change in fuel Btu value.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.417-422
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• 2003

The KOMPSAT-2 MSC(Multi-Spectral Camera), with high spatial resolution, is currently under development and will be launched in the end of 2004. A sensor model relates a 3-D ground position to the corresponding 2-D image position and describes the imaging geometry that is necessary to reconstruct the physical imaging process. The Rational Function Model (RFM) has been considered as a generic sensor model. form. The RFM is technically applicable to all types of sensors such as frame, pushbroom, whiskbroom and SAR etc. With the increasing availability of the new generation imaging sensors, accurate and fast rectification of digital imagery using a generic sensor model becomes of great interest to the user community. This paper describes the procedure to generation of the RPC (Rational Polynomial Coefficients) for KOMPSAT-2 MSC.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.413-418
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• 2003

In this paper, a new multirate optimal finite impulse response (FIR) filter is proposed for the signal reconstruction in the nosy filter bank systems. The multirate optimal FIR filter replaces the conventional synthesis filters and the Kalman synthesis filter. First, the generic linear model is derived from the multirate state space model for an autoregressive (AR)input signal. Second, the multirate optimal FIR filter is derived from the multirate generic linear model using the minimum variance criterion. This paper also provides numerical examples and results. The simulation results illustrate that the performance is improved compared with conventional synthesis filters and the proposed filter has advantages over the Kalman synthesis filter.