• Clean Technology
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• v.22 no.1
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• pp.35-44
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• 2016

In this study, a computational chemistry methodology called as molecular modeling was been applied to explain several experiment results mechanistically. The reaction chosen for this study was to remove carbon dioxide, known as a primary greenhouse gas, by an epoxide via the carbon dioxide fixation to produce carbonates. This reaction inherently needs the use of catalysts because it has a significantly high activation barrier (55~59 kcal/mol). Among various types of catalysts, we studied in zeolitic imidazolate framework 90 (ZIF-90)/ionic liquid immobilized ZIF-90 (IL-ZIF-90), polystyrene-supported quaternized ammonium salt, KI/KI-glycine, and dimethylethanolamine (DMEA). First, probable reaction pathways were proposed based on calculated energetics by computational chemistry. The energetics was then used for the thermodynamic interpretation on the activity of catalysts. In the case of ZIF-90/IL-ZIF-90 and KI/KI-glycine, IL-ZIF-90 and KI-glycine showed better yields compared to their counterparts. The calculation proposed interesting results that it is not from the lowering of activation energy but from the unstable intermediates of ZIF-90 and KI-glycine. For DMEA, the calculated activation energy was ~42 kcal/mol, much lower than that of the non-catalytic reaction. A possible reaction pathway was located to confirm the interaction between −NH group from ammonium and oxygen from epoxide for polystyrene-supported quaternized ammonium salt.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.523-533
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• 2022

This paper presents a two-stage spatio-spectral fusion method (2SSFM) based on area-to-point regression kriging (ATPRK) to enhance spatial and spectral resolutions using multi-sensor satellite images with complementary spatial and spectral resolutions. 2SSFM combines ATPRK and random forest regression to predict spectral bands at high spatial resolution from multi-sensor satellite images. In the first stage, ATPRK-based spatial down scaling is performed to reduce the differences in spatial resolution between multi-sensor satellite images. In the second stage, regression modeling using random forest is then applied to quantify the relationship of spectral bands between multi-sensor satellite images. The prediction performance of 2SSFM was evaluated through a case study of the generation of red-edge and short-wave infrared bands. The red-edge and short-wave infrared bands of PlanetScope images were predicted from Sentinel-2 images using 2SSFM. From the case study, 2SSFM could generate red-edge and short-wave infrared bands with improved spatial resolution and similar spectral patterns to the actual spectral bands, which confirms the feasibility of 2SSFM for the generation of spectral bands not provided in high spatial resolution satellite images. Thus, 2SSFM can be applied to generate various spectral indices using the predicted spectral bands that are actually unavailable but effective for environmental monitoring.

• Journal of Educational Research in Mathematics
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• v.26 no.1
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• pp.47-62
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• 2016

Cultivating mathematical creativity is one of the aims in the recently revised mathematics curricular. However, there have been lack of researches on how to nurture mathematical creativity for ordinary students. Perspective of Realistic Mathematics Education(RME), which pursues education of creative person as the ultimate goal of mathematics education, could be useful for developing principles and methods for cultivating mathematical creativity. This study reanalyzes RME from the points of view in mathematical creativity education. Major findings are followed. First, students should have opportunities for mathematical creation through mathematization, while seeking and creating certainty. Second, it is vital to begin with realistic contexts to guarantee mathematical creation by students, in which students can imagine or think. Third, students can create mathematics in realistic contexts by modelling. Fourth, students create the meaning of 'model of(MO)', which models the given context, the meaning of 'model for(MF)', which models formal mathematics. Then, students create MOs and MFs that are equivalent to the intial MO and MF given by textbook or teacher. Flexibility, fluency, and novelty could be employed to evaluate the MOs and the MFs created by students. Fifth, cultivation of mathematical creativity can be supported from development of local instructional theories by thought experiment, its application, and reflection. In conclusion, to employ the education model of cultivating mathematical creativity by RME drawn in this study could be reasonable when design mathematics lessons as well as mathematics curriculum to include mathematical creativity as one of goals.

• Food Engineering Progress
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• v.21 no.2
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• pp.132-137
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• 2017

The purpose of this study was to optimize dough properties using response surface methodology (RSM) and to demonstrate the performances of dough prepared under optimized conditions. Dough mixed with yeast, margarine, salt, sugar and wheat flour was prepared by fermentation process. Hardness, cohesiveness and springiness of dough were selected as critical quality attributes. The critical formulations (yeast and water) and process (fermentation time) variables were selected as critical input variables based on preliminary experiment. Box-Behnken design (BBD) was used as RSM. As a result, the quardratic, the squared and the linear model respectively provided the most appropriate fit ($R^2$>90) and had no significant lack of fit (p>0.05) on critical quality attributes (hardness, cohesiveness and springiness). The accurate prediction of dough characteristics was possible from the selected models. It was confirmed by validation that a good correlation was obtained between the actual and predicted values. In conclusion, the methodologies using RSM in this study might be applicable to the optimization of fermented foods containing various wheat flour and yeast.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.2
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• pp.49-71
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• 2017

FRBR Library Reference Model is a consolidated model of FR Family Model - FRBR, FRAD, FRSAD developed by IFLA in early 2016. This means the creation of upper model for the consistency of FR individual models. It can be used for the expanding of the discussions on FRBR model in Korea that have been mainly discussed only for the first group of FRBR model. In addition, it can be an opportunity to apply the whole FR Family model to domestic literature in a comprehensive manner. In this study, we analyze the draft of FRBR LRM and apply the model to the Korean classic materials. There are various work, expression, and manifestation related to a work of korean classic material, so it is good to represent the structure of bibliographic information using FR Family model. We built on our experiment using $Prot{\acute{e}}g{\acute{e}}$ to design korean classic materials' ontology modeling, which propose a new orientation of korean classic materials' organizing based on FRBR LRM. As a result, we find out the applicability of the FRBR LRM model on upcoming bibliographical data control environment.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.431-447
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• 2021

Recently, the use of high-resolution satellites is increasing in many areas. In order to supply useful satellite images stably, it is necessary to establish automatic precision geometric correction technic. Geometric correction is the process that corrected geometric errors of satellite imagery based on the GCP (Ground Control Point), which is correspondence point between accurate ground coordinates and image coordinates. Therefore, in the automatic geometric correction process, it is the key to acquire high-quality GCPs automatically. In this paper, we proposed iterative precision geometry correction method. we constructed an image pyramid and repeatedly performed GCP chip matching, outlier detection, and precision sensor modeling in each layer of the image pyramid. Through this method, we were able to acquire high-quality GCPs automatically. we then improved the performance of geometric correction of high-resolution satellite images. To analyze the performance of the proposed method, we used KOMPSAT-3 and 3A Level 1R 8 scenes. As a result of the experiment, the proposed method showed the geometric correction accuracy of 1.5 pixels on average and a maximum of 2 pixels.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.2
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• pp.120-128
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• 2016

This paper describes power generation from sea waves by using linear permanent magnet generator. A buoy is placed on the ocean surface and connected to the generator. The wave energy is carried out from the movement of a buoy. An electrical conversion system is needed between the generator and the grid. For an analysis of the power system, the modeling of the linear generator and converter system was proceeded. This paper proposes vector control method for wave power generation system using linear generator. In order to verify the proposed method, simulation and experiment performed and the results support the validity of the control scheme.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1445-1456
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• 2018

The purpose of this study is to compare the quality and characteristics of matching DEMs by using KOMPSAT-3 stereo pair capture in in-track and cross-track. For this purpose, two stereo pairs of KOMPSAT-3 were collected that were taken in the same area. The two stereo pairs have similar stereo geometry elements such as B/H, convergence angle. Sensor modeling for DEM production was performed with RFM affine calibration using multiple GCPs. The GCPs used in the study were extracted from the 0.25 m ortho-image and 5 meter DEM provided by NGII. In addition, matching DEMs were produced at the same resolution as the reference DEMs for a comparison analysis. As a result of the experiment, the horizontal and vertical errors at the CPs indicated an accuracy of 1 to 3 pixels. In addition, the shapes and accuracy of two DEMs produced in areas where the effects of natural or artificial surface land were low were almost similar.

• Journal of Korea Water Resources Association
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• v.45 no.6
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• pp.545-555
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• 2012

A numerical modeling has become increasingly popular and more important to the study of water waves with a rapid advancement of computer technology. However, different types of problems are induced during simulating wave motion. One of the key problems is re-reflection to a computation domain at the incident boundary. The internal wave generating-absorbing boundary conditions have been commonly used in numerical wave models to prevent re-reflection. For the Navier-Stokes equations model, the internal wave maker using a mass source function of the continuity equation has been used to generate various types of waves. Nonetheless, almost every numerical experiment is performed in two dimensions and only a few tests have been expanded to three dimensions. More recently, a momentum source function of the Boussinesq equations is applied to generate essentially directional waves in the three dimensional Navier-Stokes equations model. In this study, the internal wave maker using a momentum source function is employed to generate targeted linear waves in the three-dimensional LES model.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1357-1369
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• 2022

Cloud removal is an essential image processing step for any task requiring time-series optical images, such as vegetation monitoring and change detection. This paper presents a two-stage cloud removal method that combines conditional generative adversarial networks (cGANs) with regression-based calibration to construct a cloud-free time-series optical image set. In the first stage, the cGANs generate initial prediction results using quantitative relationships between optical and synthetic aperture radar images. In the second stage, the relationships between the predicted results and the actual values in non-cloud areas are first quantified via random forest-based regression modeling and then used to calibrate the cGAN-based prediction results. The potential of the proposed method was evaluated from a cloud removal experiment using Sentinel-2 and COSMO-SkyMed images in the rice field cultivation area of Gimje. The cGAN model could effectively predict the reflectance values in the cloud-contaminated rice fields where severe changes in physical surface conditions happened. Moreover, the regression-based calibration in the second stage could improve the prediction accuracy, compared with a regression-based cloud removal method using a supplementary image that is temporally distant from the target image. These experimental results indicate that the proposed method can be effectively applied to restore cloud-contaminated areas when cloud-free optical images are unavailable for environmental monitoring.