• Bulletin of the Korean Mathematical Society
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• v.52 no.4
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• pp.1113-1122
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• 2015

This paper is concerned with the pattern formation of a diffusive predator-prey model with two time delays. Based upon an analysis of Hopf bifurcation, we demonstrate that time delays can induce spatial patterns under some conditions. Moreover, by use of a series of numerical simulations, we show that the type of spatial patterns is the spiral wave. Finally, we demonstrate that the spiral wave is asymptotically stable.

• Progress in Medical Physics
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• v.1 no.1
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• pp.75-84
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• 1990

We have claculated the absorbed dose distributions in water phantom irradiated by high energy photon beam. PDD (Percent Depth Dose) and Beam Profile can be represented by functions of depths and distances by using one dimensional model model based on transport theory. The parameters on scattering and absorption are evaluated by using non-linear regression process method. The values neeessary for calculation are obtained by simple experiment. The calculated values are in good agreement with the measured values.

• Journal of The Korean Association For Science Education
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• v.7 no.1
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• pp.41-51
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• 1987

The contents which is related to energy in current science textbooks of high school have been investigated. Based on the analysis of the results, we attempt to develop a model of energy curriculum on high school level.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.503-514
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• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3383-3397
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• 2023

Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.1
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• pp.47-58
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• 2019

The paper presents the results of a multi-criteria comparative evaluation of 12 feasible Russian nuclear energy deployment scenarios with thermal and fast reactors in a closed nuclear fuel cycle. The comparative evaluation was performed based on 6 performance indicators and 5 different MCDA methods (Simple Scoring Model, MAVT / MAUT, AHP, TOPSIS, PROMETHEE) in accordance with the recommendations elaborated by the IAEA/INPRO section. It is shown that the use of different MCDA methods to compare the nuclear energy deployment scenarios, despite some differences in the rankings, leads to well-coordinated and similar results. Taking into account the uncertainties in the weights within a multi-attribute model, it was possible to rank the scenarios in the absence of information regarding the relative importance of performance indicators and determine the preference probability for a certain nuclear energy deployment scenario. Based on the results of the uncertainty/sensitivity analysis and additional analysis of alternatives as well as the whole set of graphical and attribute data, it was possible to identify the most promising nuclear energy deployment scenario under the assumptions made.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.966-969
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• 2006

An optical model based on the optical thin-film theory is derived to calculate the output radiance of small molecules organic light-emitting diodes (OLEDs). We have designed the high efficiency OLEDs using the reflectance phase control of dielectric layers. It is found that OLED with a single $TiO_2$ dielectric layer is a good candidate to enhance the outcoupling efficiency and increase the color purity.

• Journal of Magnetics
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• v.9 no.2
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• pp.47-51
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• 2004

Giant magneto-impedance (GMI) effect in zero-magnetostrictive Co-based amorphous ribbons samples in their as-quenched and stress-released states as well as with intentionally induced magnetic anisotropy were investigated. Magnetic and impedance properties of the samples exhibiting different anisotropy were compared and the optimum operation conditions for the studied samples from the view-point of their utilization as a sensor element have been determined. A design of a model of magnetic field sensor and characteristics of the constructed prototype are presented.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.55.3-55.3
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• 2019

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a (75 h^-1 Mpc)³ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large (1 h^-1 Gpc)³ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

• Journal of Science Education
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• v.43 no.1
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• pp.173-193
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• 2019

An expert teachers' instruction can be helpful to other teachers because good teaching effectively guides students to develop meaningful learning. Feynman is an excellent physics lecturer as well as one of the greatest physicists of the 20th century who presented and explained physics with his unique teaching style based on his great store of knowledge. However, it is not easy to capture and visualize teaching because it is not only the complex phenomena interrelated to various factors with the content to be taught but also the tacit representation. In this study, the framework of knowledge & belief based on the integrated mental model theory was used as a tool to capture and visualize complex and tacit representation of Feynman's teaching of 'The theory of gravitation,' a chapter in The Feynman Lectures on Physics. Feynman's teaching was found to go beyond the transmission of physics concepts by showing that components of the framework of knowledge & belief were effectively intertwined and integrated in his teaching and the storyline was well-organized. On the basis of these discussions, the implications of Feynman's teaching analyzed within the framework of knowledge & belief for physics teacher education are derived. Finally, the characteristics of the framework of knowledge & belief as tools for the analysis of teaching are presented.