• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.214-216
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• 1998

Parameterizing a model is one of the most efficient ways of conducting "virtual prototying" i.e. exploring the "What if?" scenario. But it is very difficult to construct parameterized models in commercial based FEM programs, because they usually adopt the mouse inputs in their GUI, which cannot be parameterized. We consolidated a parametric modelling technique in OPERA-3d preprocessor, which is one of world leading electromagnetic analysis programs, by combining the mouse inputs in GUI with it's FORTRAN-based self script command language.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.539-544
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• 2005

In this paper, we propose the one-step least squares method based on the squared differences to estimate the parameters of the variogram used for spatial data modelling, and discuss its asymptotic efficiency. The proposed method does not require to specify lags of interest and partition lags, so that we can delete the subjectiveness and ambiguity originated from the lag selection in estimating spatial dependence.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.8 no.3
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• pp.49-62
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• 1998

본 논문은 객체 모델링 기법을 이용하여 다단계 보안 데이터베이스 응용에 대한 구조적 특징을 표현하기 위한 모델을 제시한다. 즉, 응용 영역에 대한 데이터와 보안 의미르 통합한다. 이는 응용 영역의 데이터에 대한 불법적 유출이나 수정을 방지하는 도구가 된다 . 개발한 도구를 기초로 한 구현 모델에서는 다단계 데이터베이스를 단일 보안등급 데이터베이스들로 분해한다. 인스턴스뿐만 아니라 스키마도 보호하며 속성값 다중 인스턴스화 기법을 이용하여 커버 스토리를 표현한다. 그리고 그 모델에서의 생성, 검색, 삭제, 그리고 갱신과 같은 연산 의미를 설명한다.

• Journal of the Geological Society of Korea
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• v.54 no.6
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• pp.631-640
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• 2018

To understand the formation and evolution of a sedimentary basin in basin analysis and modelling studies, it is important to analyze the thickness and age range of sedimentary layers infilling a basin. Because the compaction effect reduces the thickness of sedimentary layers during burial, basin modelling studies typically restore the reduced thickness using the relation of porosity and depth (compaction trend). Based on the compilation plots of published compaction trends of representative sedimentary rocks (sandstone, shale and carbonate), this study estimates the compaction trend ranges with exponential curves and equations. Numerical analysis of sedimentary compaction is performed to evaluate the variation of porosity and layer thickness with depth at key curves within the compaction trend ranges. In sandstone, initial porosity lies in a narrow range and decreases steadily with increasing depth, which results in relatively constant thickness variations. For shale, the porosity variation shows two phases which are fast reduction until ~2,000 m in depth and slow reduction at deeper burial, which corresponds to the thickness variation pattern of shale layers. Carbonate compaction is characterized by widely distributed porosity values, which results in highly varying layer thickness with depth. This numerical compaction analysis presents quantitatively the characteristics of porosity and layer thickness variation of each lithology, which influence on layer thickness reconstruction, subsidence and thermal effect analyses to understand the basin formation and evolution. This work demonstrates that the compaction trend is an important factor in basin modelling and underlines the need for appropriate application of porosity data to produce accurate analysis outcomes.

• Korean Journal of Geomatics
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• v.4 no.2
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• pp.39-45
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• 2004

Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.

• Computers and Concrete
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• v.12 no.3
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• pp.243-259
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• 2013

Recent developments in Artificial Intelligence (AI) and computational intelligence have made it viable in the construction industry and structural analysis. This study usesthe Adaptive Network-based Fuzzy Inference System (ANFIS) as a modelling tool to predict the strain in tie section for High Strength Self Compacting Concrete (HSSCC) deep beams. 3773 experimental data were collected. The input data andits corresponding strains in tie section as output data were recorded at all loading stages. Results from ANFIS are compared with the classical linear regression (LR). The comparison shows that the ANFIS's results are highly accurate, precise and satisfactory.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.295-301
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• 2018

This study compares optimization algorithms for efficient estimations of ship's hydrodynamic coefficients. Two constrained algorithms, the interior point and the sequential quadratic programming, are compared for the estimation. Mathematical optimization is designed to get optimal hydrodynamic coefficients for modelling a ship, and benchmark data are collected from sea trials of a training ship. A calibration for environmental influence and a sensitivity analysis for efficiency are carried out prior to implementing the optimization. The optimization is composed of three steps considering correlation between coefficients and manoeuvre characteristics. Manoeuvre characteristics of simulation results for both sets of optimized coefficients are close to each other, and they are also fit to the benchmark data. However, this similarity interferes with the comparison, and it is supposed that optimization conditions, such as designed variables and constraints, are not sufficient to compare them strictly. An enhanced optimization with additional sea trial measurement data should be carried out in future studies.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.20-26
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• 1998

Heat release data were obtained by analysis of cylinder diagrams from a test engine, naturally-aspirated small-size four-stroke DI diesel engine. These data were used to decide empirical coefficients of Whitehouse-Way's model, single zone combustion model. Finally, the comparison of calculated with experimental results was performed, and the accuracy of calculated versus experimental data of the model in predicting engine heat release and cylinder pressure was demonstrated.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.193-200
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• 2000

Modelling the dependence via random effects in censored multivariate survival data has recently received considerable attention in the biomedical literature. The random effects models model not only the conditional survival times but also the conditional hazard rate. Systematic likelihood inference for the models with random effects is possible using Lee and Nelder's (1996) hierarchical-likelihood (h-likelihood). The purpose of this presentation is to introduce Ha et al.'s (2000a,b) inferential methods for the random effects models via the h-likelihood, which provide a conceptually simple, numerically efficient and reliable inferential procedures.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.729-732
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• 2005

This paper describes a time-spatial domain model for simulating raw data acquisition of space-borne SAR system. The position, velocity and attitude information of the platform at a certain time instance is used for deriving sensor-target model. Ground target is modelled by a set of point scatters with reflectivity and two-dimensional ground coordinates. The signal received by SAR is calculated for each slow and fast time instance by integrating the reflectivity and phase values from all target point scatters. Different from frequency domain simulation algorithms, the proposed time domain algorithm can provide fully physical modelling of SAR raw data simulation without any assumptions or approximations.