• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3284-3306
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• 2018

This study proposes a method to develop an authoring system(GeoMaTree) for diverse trees that constitute a virtual landscape. The GeoMaTree system enables the simple, intuitive production of an efficient structure, and supports real-time processing. The core of the proposed system is a procedural modeling based on a mathematical model and an application that supports digital content creation on diverse platforms. The procedural modeling allows users to control the complex pattern of branch propagation through an intuitive process. The application is a multi-resolution 3D model that supports appropriate optimization for a tree structure. The application and a compatible function, with commercial tools for supporting the creation of realistic synthetic images and virtual landscapes, are implemented, and the proposed system is applied to a variety of 3D image content.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.424-429
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• 2008

Aircraft flutter analysis model consists of dynamic FE model and aerodynamic model. Dynamic FE model is composed of stiffness and mass model, and is used for the prediction of normal mode characteristics of the structure. Since aircraft flutter analysis is normally performed in the modal domain, dynamic FE model shall be constructed to describe the modal characteristics of the structure with sufficient accuracy. In this study, dynamic FE modeling method was described using full airframe FE model and structural and system weight data for aircraft flutter analysis. In addition, full airframe dynamic FE model for composite small aircraft was constituted for normal mode and flutter analysis, and the mass modeling results were compared with the target weight data to validate the mass modeling method proposed. Finally, full airframe flutter analysis of composite small aircraft was performed with the dynamic FE model and the aerodynamic model composed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.339-344
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• 2011

In the past much effort has been made to utilize advanced computational fluid dynamic (CFD) programs for aeroelastic simulations and analysis. However, it is limited in the field of unsteady aeroelasticity due to enormous size of computer memory and unreasonably long CPU time. Recently, AAEMS(Aerodynamics is Aeroelasticity minus Structure) was developed for linear time-invariant, coupled fluid-structure systems. In this paper, to demonstrate further the efficiency and accuracy of the new model reduction method, we successfully examine AGARD 445.6 wing modeled by FLUENT CFD, FSIPRO3D and NASTRAN FEM(Finite Element Method) programs. Using the ROM(Reduced Order Modeling) one can predict flutter boundary as a function of the dynamic pressure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.04a
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• pp.71-78
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• 1993

This study serves as a part for the development of an integrated structural design system. Efficient data management is essential in engineering computer applications where the volume of data is large and the data flow and sharing are required. From a viewpoint of computer application, building structures can be considered to be a mass ofdata. The centralized database(CDB) and database management system frees the application from the details of managing data storage and retrieval while providing a common pool of information. For this, systematic information analysis and modeling have to be preceded. In this paper we described the result of database modeling of building structure.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.378-386
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• 1999

The integrated system for the structural analysis of space frame is made up 4 modules ; pre-process module, structural analysis module, optimum member design module and post-process module. Re-process module of these 4 modules involves data input module and structure modeling module. This study is to develope an efficient modeling program as a basic for development of pre-process module. This modeling program generates geometric information of space frame and performs the input fie form for structure analysis only by input general data. User can mode1 space frame efficiently within shut time by using this program.

• Journal of Integrative Natural Science
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• v.7 no.4
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• pp.234-240
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• 2014

C-C chemokine receptor type 4 (CCR4) is a chemokine receptor with seven transmembrane helices and it belongs to the GPCR family. It plays an important role in asthma, lung disease, atopic dermatitis, allergic bronchopulmonary aspergillosis, cancer, inflammatory bowel disease, the mosquito-borne tropical diseases, such as dengue fever and allergic rhinitis. Because of its role in wide spectrum of disease processes, CCR4 is considered to be an important drug target. Three dimensional structure of the protein is essential to determine the functions. In the present study homology modeling of human CCR4 was performed based on crystal structure of CCR5 chemokine receptor. The generated models were validated using various parameters. Among the generated homology models the best one is selected based on validation result. The model can be used for performing further docking studies to identifying the critical interacting residues.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2305-2307
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• 2000

In this paper we propose a Neuro-Fuzzy modeling method using mGA for complex nonlinear system. mGA has more effective and adaptive structure than sGA with respect to using the changeable-length string. This paper suggest a new coding method for applying the model's input and output data to the number of optimul rules of fuzzy models and the structure and parameter identifications of membership function simultaneously. The proposed method realize optimal fuzzy inference system using the learning ability of Neural network. For fine-tune of the identified parameter by mGA, back-propagation algorithm used for optimulize the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through compare with ANFIS.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.153-158
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• 1995

In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed fuzzy GMDH modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) algorithm and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH algorithm and fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnaceare those for sewage treatment process are used for the purpose of evaluating the performance of the proposed fuzzy GMDH modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2653-2655
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• 2001

In this paper, we proposed a method of modeling a system using Fuzzy Equalization(FE) and Genetic Algorithm(GA). The initial model is constructed using FE. The antecedent parameters and the rules in fuzzy logic are tuned by GA. The proposed system minimizes the modeling error and the size of structure. The process of building membership functions using PDF(Probability Density Function) and GA tunes the antecedent parameter and rules for minimizing the error and structure. The usefulness of proposed method is demonstrated by applying to Box-Jenkins furnace data.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.4
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• pp.344-348
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• 2002

As microelectronics technology continues to progress, there is also a continuous demand on highly integration and miniaturization of systems. For example, it is desirable to package several integrated circuits together in multilayer structure, such as multichip modules, to achieve higher levels of compactness and higher performance. Passive components (i.e., capacitors, resistors, and inductors) are very important fort many MCM applications. In addition, the low-temperature co-fired ceramic (LTCC) process has considerable potential for embedding passive components in a small area at a low cost. In this paper, we investigate a method of statistically modeling integrated passive devices from just a small number of test structures. A set of LTCC inductors is fabricated and their scattering parameters (s-parameters) are measured for a range of frequencies from 50MHz to 5GHz. An accurate model for each test structure is obtained by using a building block based modeling methodology and circuit parameter optimization using the HSPICE circuit simulator.