• Korean System Dynamics Review
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• v.10 no.1
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• pp.5-32
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• 2009

This paper revisited the key advances on System Dynamics modeling about traditional macro-economic models and economic growth structures, and then tries to elaborate a new model based on the endogenous growth theory that incorporates new growth factors, relevant to knowledge/technology as well as the Environment, into traditional growth models. Accordingly, the new model augments the acceleration and multiplier loops and the balancing ones representing market clearing mechanism with a simple numerical example. The authors thus provides macroeconomic System Dynamics analysts with a milestone to model macro-economic structures reflecting on traditional and cutting-edge theories on sustainable economic growth and general equilibrium modeling.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.1
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• Korean Journal of Computational Design and Engineering
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• v.3 no.1
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• pp.1-14
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• 1998

This paper introduces non-manifold offsetting operations, which add or remove a uniform thickness from a given non-manifold model. Since these operations can be applied to not only solids but also wireframe or sheet objects, they are potentially useful for pipeline modeling, sheet metal and plastic part modeling, tolerance analysis, clearance checking, constant-radius rounding and filleting of solids, converting of abstracted models to solids, HC too1 path generation and so on. This paper describes mathematical properties and algorithms for non-manifold offsetting. In this algorithm, a sufficient set of tentative faces are generated first by offsetting all or a subset of the vertices, edges and faces of the non-manifold model. And then they are merged into a model using the Boolean operations. Finally topological entities which are within offset distance are removed. The partially modified offsetting algorithms for wireframes or sheets are also discussed in order to provide more practical offset models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.385-390
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• 1997

In recent years there has been an increasing emphasis on shortening design cycles for bringing products to market. This requires the development of computer aided engineering tools which allow analysts to quickly evaluate the effect of design changes on noise, vibration, and harshness. Statistical Energy Analysis (SEA) modeling is a valuable tool for predicting noise and vibration as SEA models are inherently simpler and more robust than deterministic models. SEA modeling can be combined with design sensitivity analysis (DSA) to identify design changes which give the largest performance benefit. This paper describes SEA modeling of an equipment cab. SEA predictions are compared to test data, showing good agreement. The use of design sensitivity analysis in improving cab design is then demonstrated.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.259-260
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• 2023

The rapid urbanization and modernization observed in countries like Myanmar have led to significant concerns regarding traffic congestion, especially in urban areas. This study focuses on the analysis and revitalization of urban transport in selected areas of Myanmar. The core of urban transportation planning lies in travel forecasting, which employs models to predict future traffic patterns and guide decisions related to road capacity, transit services, and land use policies. Travel demand modeling involves a series of mathematical models that simulate traveler behavior and decision-making within a transportation system, including highways, transit options, and policies. The paper offers an overview of the traditional four-step transportation modeling system, utilizing a simplified transport network in the context of Mandalay City, Myanmar.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.184-191
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• 2020

Avionics System Integration Laboratory is the integrated test environment for integration and verification of avionics systems. When real equipment can not be used in the laboratory for various reasons, software models should be needed. Because there hasn't been any standardized method for the models so that it is difficult to reuse the developed models, the need for a framework to develop the avionics software models was emerged. We adopted DEVS(discrete event system specification) formalism as the standardized modeling method for the avionics software models. Due to DEVS formalism is based on event-driven algorithm, it doesn't accord a legacy system which has sequential and periodic algorithms. In this paper, we propose real-time event-driven modeling and simulation method for SIL to overcome these restrictions and to maximize reusability of avionics models through the analysis of the characteristics and the limitations of avionics models.

• Journal of Korean Library and Information Science Society
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• v.36 no.2
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• pp.49-68
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• 2005

The purpose of this study is to examine the research trends and their experiment results on the applications of the language models for information retrieval. We reviewed the previous studies with the following categories: (1) the first generation of language modeling information retrieval (LMIR) experiments which are mainly focused on comparing the language modeling information retrieval with the traditional retrieval models in their retrieval performance, and (2) the second generation of LMIR experiments which are focused on comparing the expanded language modeling information retrieval with the basic language models in their retrieval performance. Through the analysis of the previous experiments results, we found that (1) language models are outperformed the probabilistic model or vector space model approaches, and (2) the expended language models demonstrated better results than the basic language models in their retrieval performance.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.3
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• pp.503-515
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• 2018

In this research, the three-dimensional structural and colorimetrical modeling of yarn-dyed woven fabrics was conducted based on the Kubelka-Munk theory (K-M theory) for their accurate color predictions. In the K-M theory for textile color formulation, the absorption and scattering coefficients, denoted K and S, respectively, of a colored fabric are represented using those of the individual colorants or color components used. One-hundred forty woven fabric samples were produced in a wide range of structures and colors using red, yellow, green, and blue yarns. Through the optimization of previous two-dimensional color prediction models by considering the key three-dimensional structural parameters of woven fabrics, three three-dimensional K/S-based color prediction models, that is, linear K/S, linear log K/S, and exponential K/S models, were developed. To evaluate the performance of the three-dimensional color prediction models, the color differences, ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and ${\Delta}E_{CMC(2:1)}$, between the predicted and the measured colors of the samples were calculated as error values and then compared with those of previous two-dimensional models. As a result, three-dimensional models have proved to be of substantially higher predictive accuracy than two-dimensional models in all lightness, chroma, and hue predictions with much lower ${\Delta}L^*$, ${\Delta}C^*$, ${\Delta}h^{\circ}$, and the resultant ${\Delta}E_{CMC(2:1)}$ values.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.62-64
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• 1996

Two current approaches for modeling the vector magnetic hysteretic process are the vector Preisach models and those models based on a system of noninteracting pseudo-particles. The pseudo-particles are intended to mimic the average behavior of real media particles. The simplest switching mechanisms of pseudoparticles is the Stoner-Wholfarth model. The Preisach models are quite precise in specifying the experimental input to the models. The vector properties of the Preisach models are, however, inadequate. This is partly because of the questionable assumptions used in coupling the various vector hysteresis components. Also these models do not include reversible magnetization changes. Unlike Preisach counterpart, the Stoner-Wholfarth model is inherently vector in nature. This is because spatial distribution and switching mechanisms are imposed on the system of pseudo-particles, so they come closer to representing the physical reality. The lack of interaction between pseudo-particles exclude the usefulness of the Stoner-Wholfarth model for small fields when the medium is traversing minor loops. The present work is an attempt at combining the advantages of above two models into one composite model, including the effect of particle interaction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.297-311
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• 2021

Around the world, there is an increasing interest in Digital Twin cities. Although geospatial data is critical for building a digital twin city, currently-established spatial data cannot be used directly for its implementation. Integration of geospatial data is vital in order to construct and simulate the virtual space. Existing studies for data integration have focused on data transformation. The conversion method is fundamental and convenient, but the information loss during this process remains a limitation. With this, standardization of the data model is an approach to solve the integration problem while hurdling conversion limitations. However, the standardization within indoor space data models is still insufficient compared to 3D building and city models. Therefore, in this study, we present a comparative analysis of data models commonly used in indoor space modeling as a basis for establishing a generic indoor space feature model. By comparing five models of IFC (Industry Foundation Classes), CityGML (City Geographic Markup Language), AIIM (ArcGIS Indoors Information Model), IMDF (Indoor Mapping Data Format), and OmniClass, we identify essential elements for modeling indoor space and the feature classes commonly included in the models. The proposed generic model can serve as a basis for developing further indoor feature models through specifying minimum required structure and feature classes.