• Parasites, Hosts and Diseases
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• v.52 no.1
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• pp.105-109
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• 2014

Plasmodium falciparum malaria is a major public health problem in Thailand due to the emergence of multidrug resistance. The understanding of genetic diversity of malaria parasites is essential for developing effective drugs and vaccines. The genetic diversity of the merozoite surface protein-1 (PfMSP-1) and merozoite surface protein-2 (PfMSP-2) genes was investigated in a total of 145 P. falciparum isolates collected from Mae Sot District, Tak Province, Thailand during 3 different periods (1997-1999, 2005-2007, and 2009-2010). Analysis of genetic polymorphisms was performed to track the evolution of genetic change of P. falciparum using PCR. Both individual genes and their combination patterns showed marked genetic diversity during the 3 study periods. The results strongly support that P. falciparum isolates in Thailand are markedly diverse and patterns changed with time. These 2 polymorphic genes could be used as molecular markers to detect multiple clone infections and differentiate recrudescence from reinfection in P. falciparum isolates in Thailand.

• The Mathematical Education
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• v.46 no.2 s.117
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• pp.173-192
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• 2007

We define mathematical learning as a process of overcoming framing difference of teachers and students, two main subjects in a mathematics class. We have reached this definition to the effect that we can grasp a mathematical classroom per so and understand students' mathematical learning in the context. We could clearly understand the process in which the framing differences are overcome by analyzing mutual negotiation of informants in specific cultural models, both in its form as well as in its meaning. We review both of the direct and indirect forms of negotiation while keeping track of 'evolution of subject' in terms of content of negotiation. More specifically, we discuss direct negotiation briefly and review indirect negotiation from three distinct themes of (1) argument structure, (2) revoicing, and (3) development patterns and narrative structure of proof. In addition, we describe the content of negotiation under the title of 'Evolution of Subject.' We found that major modes of mutual negotiation are inter-reference and appropriation while the product of continued negotiation is inter-resemblance.

• Computers and Concrete
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• v.25 no.6
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• pp.517-523
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• 2020

An experimental system on three point bending notched beams was established to study the fracture process of concrete. In this system, the acoustic emission (AE) was used to build the cumulative generation order (AGO) and dynamically track the process of microcrack evolution in concrete. A grey-cusp catastrophe model was built based on AE parameters. The results show that the concrete beams have significant catastrophe characteristic. The developed grey-cusp catastrophe model, based on AGO, can well describe the catastrophe characteristic of concrete fracture process. This study also provides a theoretical and technical support for the application of AE in concrete fracture prediction.

• Journal of Astronomy and Space Sciences
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• v.24 no.1
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• pp.1-30
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• 2007

We present the Pre-Main Sequence (PMS) evolutionary tracks of stars with $0.065{\sim}5.0M_{\odot}$. The models were evolved from the PMS stellar birthline to the onset of hydrogen burning in the core. The convective turnover timescales which enables an observational test of theoretical model, particulary in the stellar dynamic activity, are also calculated. All models have Sun-like metal abundance, typically considered as the stars in the Galactic disk and the star formation region of Population I star. The convection phenomenon is treated by the usual mixing length approximation. All evolutionary tracks are available upon request.

• ETRI Journal
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• v.34 no.4
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• pp.645-648
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• 2012

An incremental subspace learning scheme to recover lost speech segments online is presented. Our contributions in this work are twofold. First, the recovery problem is transformed into an interpolation problem of the time-varying gains via nonnegative matrix factorization. Second, incremental nonnegative matrix factorization is employed to allow online processing and track the evolution of speech statistics. The effectiveness of the proposed scheme is confirmed by the experiment results.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.4
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• pp.17-29
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• 2004

Internal waves are computed using a ghost fluid method on an unstructured grid. Discontinuities in density and dynamic pressure are captured in one cell without smearing or oscillations along a multimaterial interface. A time-accurate incompressible Navier-Stokes/Euler solver is developed based on a three-point backward difference formula for the physical time marching. Artificial compressibility is introduced with respect to pseudotime and an implicit method is used for the pseudotime iteration. To track evolution of an interface, a level set function is coupled with the governing equations. Roe's flux difference splitting method is used to calculate numerical fluxes of the coupled equations. To get higher order accuracy, dependent variables are reconstructed based on gradients which are calculated using Gauss theorem. For each edge crossing an interface, dynamic pressure is assigned for a ghost node to enforce the continuity of total pressure along the interface. Solitary internal waves are computed and the results are compared with other computational and experimental results.

• 한국연소학회:학술대회논문집
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• 2015.12a
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• pp.265-266
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• 2015

The multi-environment PDF model coupled with flamelet generated manifolds(FGM) has been developed for a large eddy simulation of turbulent partially premixed lifted flame. This approach has a capability to realistically account for the transport and evolution of probability density function for mixture fraction and progress variable with the manageable computational burden. Using the tabulated chemistry, it is possible to track radical distributions which is important to predict autoignition process with the vitiated coflow environment. Numerical results indicate that the present yields the good agreement with experimental data in terms of mixture fraction, temperature, and species mass fractions.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.53.3-53.3
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• 2019

Recent work by Ravanbakhsh et al. (2017), Mathuriya et al. (2018) showed that convolutional neural networks (CNN) can be trained to predict cosmological parameters from the visual shape of the large scale structure, i.e. the filaments, clusters and voids of the cosmic density field. These preliminary works used the dark matter density field at redshift zero. We build upon these works by considering realistic mock galaxy catalogues that mimic true observations. We construct light-cones that span the redshift range appropriate for current and near future cosmological surveys such as LSST, EUCLID, WFIRST etc. In summary, we propose a novel multi-image input CNN to track the evolution in the morphology of large scale structures over cosmic time to constrain cosmology and the expansion history of the Universe.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.78.3-78.3
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• 2019

We develop a novel technique that can constrain the evolutionary track of the epoch of reionization (EoR) by applying the convolutional neural network (CNN) to the 21-cm differential brightness temperature. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm map between z=6-13. We design a CNN architecture that predicts the volume-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction has a good agreement with its truth value even after smoothing the 21-cm map with somewhat realistic choices of beam size and the frequency bandwidth of the Square Kilometre Array (SKA). Our technique could be further utilized to denoise the 21-cm map or constrain the properties of the radiation sources.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.147-155
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• 2022

The accumulated ice and snow during the operation of aircraft and railway vehicles can degrade aerodynamic performance or damage the major components of vehicles. Therefore, it is crucial to predict the temporal growth of ice for operational safety. Numerical simulation of ice is widely used owing to the fact that it is economically cheaper and free from similarity problems compared to experimental methods. However, numerical simulation of ice generally divides the analysis into multi-step and assumes the quasi-steady assumption that considers every time step as steady state. Although this method enables efficient analysis, it has a disadvantage in that it cannot track continuous ice evolution. The purpose of this study is to construct a surrogate model that can predict the temporal evolution of ice shape using reduced-order modeling. Reduced-order modeling technique was validated for various ice shape generated under 100 different icing conditions, and the effect of the number of training data and the icing conditions on the prediction error of model was analyzed.