• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1096-1107
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• 2019

In this paper, we present an ontology-based approach to labeling influential topics of scientific articles. First, to look for influential topics from scientific article, topic modeling is performed, and then social network analysis is applied to the selected topic models. Abstracts of research papers related to data mining published over the 20 years from 1995 to 2015 are collected and analyzed in this research. Second, to interpret and to explain selected influential topics, the UniDM ontology is constructed from Wikipedia and serves as concept hierarchies of topic models. Our experimental results show that the subjects of data management and queries are identified in the most interrelated topic among other topics, which is followed by that of recommender systems and text mining. Also, the subjects of recommender systems and context-aware systems belong to the most influential topic, and the subject of k-nearest neighbor classifier belongs to the closest topic to other topics. The proposed framework provides a general model for interpreting topics in topic models, which plays an important role in overcoming ambiguous and arbitrary interpretation of topics in topic modeling.

• Genomics & Informatics
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• v.20 no.2
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• pp.22.1-22.9
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• 2022

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant's effect was contemplated as a weighted sum of the delta and omicron variants' transmission rate and tuned using a hyperparameter k. Our models' performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don't see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.2
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• pp.144-151
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• 2015

The present study proposes a method for modeling a SONAR transducer with dual resonance. The Butterworth van-Dyke (BVD) model, a conventional SONAR transducer modeling method, can model only one resonance point. Hence, to address its disadvantage and to model the dual resonance, a dual resonance BVD model consisting of two serial BVD models is proposed. The two BVD models are connected in a series, and each simulate resonance at low frequency and high frequency, which allows the modeling of two resonance points. Eight elements compose the equivalent circuit by connecting the BVD models in a series, which is twice as great as that of the existing BVD model. The element value of the dual resonance BVD model is extracted by using the particle swarm optimization method. Analysis was also performed to identify the effects of changes in the value of elements that compose the equivalent circuit on the impedance characteristics of the equivalent circuit through simulation in which element values varied.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.2
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• pp.18-24
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• 2010

A correct and accurate model of optical data storage systems is very important in development and performance evaluation of various data detection algorithms. In this paper, we present an nonlinear modeling scheme of a super-resolution near-field structure (Super-RENS) read-out signal using the canonical piecewise-linear (PWL) and the second-order Volterra models. Nonlinear equalizers may be developed on the basis of the information obtained from this nonlinear modeling. To mitigate the nonlinear inter-symbol interference (ISI), we proposed a new nonlinear equalizer for Super-RENS discs. Its validity is tested with the RF signal samples obtained from a Super-RENS disc. The experiment results verified the possibility that the canonical PWL and the second-older Volterra models can be utilized for nonlinear modeling of Super-RENS systems. The proposed equalizers are superior to the one without equalization in terms of bit error rate (BER).

• Journal of the Korean Ceramic Society
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• v.54 no.6
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• pp.506-510
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• 2017

One of the characteristics of polycrystalline graphene that determines its material properties is grain size. Mechanical properties such as Young's modulus, yield strain and tensile strength depend on the grain size and show a reverse Hall-Petch effect at small grain size limit for some properties under certain conditions. While there is agreement on the grain size effect for Young's modulus and yield strain, certain MD simulations have led to disagreement for tensile strength. Song et al. showed a decreasing behavior for tensile strength, that is, a pseudo Hall-Petch effect for the small grain size domain up to 5 nm. On the other hand, Sha et al. showed an increasing behavior, a reverse Hall-Petch effect, for grain size domain up to 10 nm. Mortazavi et al. also showed results similar to those of Sha et al. We suspect that the main difference of these two inconsistent results is due to the different modeling. The modeling of polycrystalline graphene with regular size and (hexagonal) shape shows the pseudo Hall-Petch effect, while the modeling with random size and shape shows the reverse Hall-Petch effect. Therefore, this study is conducted to confirm that different modeling is the main reason for the different behavior of tensile strength of the polycrystalline structures. We conducted MD simulations with models derived from the Voronoi tessellation for two types of grain size distributions. One type is grains of relatively similar sizes; the other is grains of random sizes. We found that the pseudo Hall-Petch effect and the reverse Hall-Petch effect of tensile strength were consistently shown for the two different models. We suspect that this result comes from the different crack paths, which are related to the grain patterns in the models.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.11-22
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• 2012

This paper proposes for practical engineers a lightweight modeling and simulation environment for continuous system models specified in ordinary differential equations, which are time-domain specification of such systems. We propose a block-oriented specification formalism that has two levels: one for atomic behavior and the other the structure of models. Also we provide with a simulation framework, called BlockSim++, which make models specified in the block-oriented formalism be easily translated in object-oriented program that runs with the proposed simulation framework. The proposed formalism and framework has advantage of reuse such that it can be easily integrated into application programs and heterogeneous simulators. We illustrates the usefulness of the proposed framework by a simple hybrid modeling simulation example.

• Journal of the Korean Geotechnical Society
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• v.19 no.3
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• pp.33-38
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• 2003

Marine sediment capping is a technique where clean sand is placed over contaminated sediment to reduce the migration of contaminants to the environment. The design of in-situ caps placed over marine sediment must take into consideration the self-weight consolidation of the cap and the consolidation of the sediment as a result of adding the cap layer. Centrifuge tests were adopted to simulate the effects of consolidation settlement of capped marine sediment caused by the placement of a clean sand layer. The modeling of models technique was utilized to verify the correct modeling procedures used in this study. Two centrifuge tests were conducted with the same boundary conditions at different gravitational accelerations of 100 g and 50 g. There was good agreement between these tests. It can be concluded that the centrifuge experiment is able to model consolidation settlement of capped marine sediment.

• Geophysics and Geophysical Exploration
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• v.8 no.3
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• pp.207-217
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• 2005

We present a new approximate formulation of the integral equation (IE) method for models with variable background conductivity. This method overcomes the standard limitation of the conventional If method related to the use of a horizontally layered background only. The new approximate IE method still employs the Green's functions for a horizontally layered 1-D model. However, the new method allows us to use an inhomogeneous background with the IE method. The method was carefully tested for modeling the EM field for complex structures with a known variable background conductivity. It can find wide application in modeling EM data for multiple geological models with some common geoelectrical features, like a known inhomogeneous overburden, or salt dome structures.