• Journal of the Korean Chemical Society
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• v.34 no.1
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• pp.69-75
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• 1990

An ion-association chromatography was applied for the separation and determination of individual rare earth elements (REE) contained in mineral monazite. Prior to the determination, the group separation of REE was achieved by a cation exchange column of Dowex 5OW-X8 resin. The quantitative recovery of REE by the resin column, free from coexisting elements in monazite, was confirmed with radioactive tracers as well as with ICP-MS. Individual REE at ppm level was separated on reversed-phase column ($\mu$-Bondapak $C_{18}$) using gradient elution from 0.05 to 0.3 M $\alpha$-hydroxyisobutyric acid at pH 4.6. The individual REE was detected at 546 nm following post-column reaction with PAR (4-(2-pyridylazo)-resorcinol monosodium salt).

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.113-127
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• 2021

The purpose of this study is to propose a personalized book recommendation system to promote the use of university libraries. In particular, unlike many recommended services that are based on existing users' preferences, this study proposes a method that derive evaluation metrics using individual users' book rental history and tendencies, which can be an effective alternative when users' preferences are not available. This study suggests models using two matrix decomposition methods: Singular Value Decomposition(SVD) and Stochastic Gradient Descent(SGD) that recommend books to users in a way that yields an expected preference score for books that have not yet been read by them. In addition, the model was implemented using a user-based collaborative filtering algorithm by referring to book rental history of other users that have high similarities with the target user. Finally, user evaluation was conducted for the three models using the derived evaluation metrics. Each of the three models recommended five books to users who can either accept or reject the recommendations as the way to evaluate the models.

• Journal of Science Education
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• v.47 no.1
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• pp.37-51
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• 2023

This study explored the factors influencing major satisfaction and academic satisfaction of science education major students at the College of Education using machine learning models, random forest, gradient boosting model, and SHAP. Analysis results showed that the performance of the gradient boosting model was better than that of the random forest, but the difference was not large. Factors influencing major satisfaction include 'satisfaction with science teachers in high school corresponding to the subject of one's major', 'motivation for teaching job', and 'age'. Through the SHAP value, the influence of variables was identified, and the results were derived for the group as a whole and for individual analysis. The comprehensive and individual results could be complementary with each other. Based on the research results, implications for ways to support pre-service science teachers' major and academic satisfaction were proposed.

• Journal of The Geomorphological Association of Korea
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• v.19 no.2
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• pp.99-111
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• 2012

The purpose of this study is to identify the change of geographical (or geomorphological) location environment of the dwelling site and its cause in Daejon Basin during transition from the Bronze Age to the Proto Three Kingdoms Period. In order to achieve this goal, it was divided into (1) 'comparison of the total number of dwelling sites of a group of remains (or high-density dwelling remains)' and (2) 'comparison of the total number of dwelling sites in certain remains including locations of dwelling of two periods' and location environment was compared to each other in aspects of altitude, gradient, 'distance from the river of water available for use' and 'the difference between the highest altitude and lowest altitude of river bed of water available for use' based on change of period. The results were as follows: 1. looking at a change of individual factors, the altitude was elevated and the gradient was increased. The distance from the river of water available for use was decreased or increased in case of 'small scale river' and it was very little difference or increased in case of 'medium scale river'. The difference between the highest altitude and lowest altitude of river bed of water available for use was increased in case of 'small scale river' and it was increased or decreased in case of 'medium scale river'. If comparing the individual factors to each other, the increase and decrease of altitude, gradient and the difference between the highest altitude and lowest altitude of river bed of water available for use have the similar pattern. Especially, it was shown that the increase of gradient affected the increase of altitude and the difference between the highest altitude and lowest altitude of river bed of water available for use. In addition, it was shown that the increase and decrease of distance from the river of water available for use had the different pattern from those of altitude, gradient and 'the difference between the highest altitude and lowest altitude of river bed of water available for use'. 3. With above results, it was thought that combination of micro landform characteristics (eg. Characteristics of gradient) of low hills distributed within Daejeon Basin and rich aquatic environment surrounding the low hills affected the selection of location of dwelling sites at the time. Especially, it was shown that 'gradient and distance from the river of water available for use' were relatively more important factors for the inhabitants at the time to select the location of dwelling sites compared to 'altitude and difference between the highest altitude and lowest altitude of river bed of water available for use' upon selecting the location of dwelling.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.461-479
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• 2006

This paper derives joint and conditional Lagrange multiplier tests based on Double-Length Artificial Regression(DLR) for testing functional form and/or the presence of individual(time) effect in a panel regression model. Small sample properties of these tests are assessed by Monte Carlo study, and comparisons are made with LM tests based on Outer Product Gradient(OPG). The results show that the proposed DLR based LM tests have the most appropriate finite sample performance.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.443-458
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• 2014

An extreme learning machine (ELM) is a recently proposed learning algorithm for a single-layer feed forward neural network. In this paper we studied the ensemble of ELM by using a bagging algorithm for facial expression recognition (FER). Facial expression analysis is widely used in the behavior interpretation of emotions, for cognitive science, and social interactions. This paper presents a method for FER based on the histogram of orientation gradient (HOG) features using an ELM ensemble. First, the HOG features were extracted from the face image by dividing it into a number of small cells. A bagging algorithm was then used to construct many different bags of training data and each of them was trained by using separate ELMs. To recognize the expression of the input face image, HOG features were fed to each trained ELM and the results were combined by using a majority voting scheme. The ELM ensemble using bagging improves the generalized capability of the network significantly. The two available datasets (JAFFE and CK+) of facial expressions were used to evaluate the performance of the proposed classification system. Even the performance of individual ELM was smaller and the ELM ensemble using a bagging algorithm improved the recognition performance significantly.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.3
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• pp.186-199
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• 2013

We pose pattern classification as a density estimation problem where we consider mixtures of generative models under partially labeled data setups. Unlike traditional approaches that estimate density everywhere in data space, we focus on the density along the decision boundary that can yield more discriminative models with superior classification performance. We extend our earlier work on the recursive estimation method for discriminative mixture models to semi-supervised learning setups where some of the data points lack class labels. Our model exploits the mixture structure in the functional gradient framework: it searches for the base mixture component model in a greedy fashion, maximizing the conditional class likelihoods for the labeled data and at the same time minimizing the uncertainty of class label prediction for unlabeled data points. The objective can be effectively imposed as individual mixture component learning on weighted data, hence our mixture learning typically becomes highly efficient for popular base generative models like Gaussians or hidden Markov models. Moreover, apart from the expectation-maximization algorithm, the proposed recursive estimation has several advantages including the lack of need for a pre-determined mixture order and robustness to the choice of initial parameters. We demonstrate the benefits of the proposed approach on a comprehensive set of evaluations consisting of diverse time-series classification problems in semi-supervised scenarios.

• Journal of The Korean Astronomical Society
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• v.40 no.1
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• pp.9-16
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• 2007

We examine the morphology and luminosity distribution of a strongly warped spiral galaxy PGC 20348 by conducting a detailed BVI CCD surface photometry using BOAO 1.8m telescope. The radial surface brightness shows a break at warp radius $(r_{\omega})$ with a shallow gradient in the inner disk and a steeper gradient in the outer disk. The luminosity of east side of the disk is ${\sim}0.5$ mag fainter than the west side at r > $r_{\omega}$. The reason for the asymmetric luminosity distribution is thought to be the asymmetric flarings that result in the formation of a large diffuse region at the edge of the east disk and a smaller diffuse region at the west disk. The vertical luminosity profiles show a thick disk component whose scale heights increase with increasing galactocentric distances. The warp of PGC 20348 seems to be made by the tidal interactions with the two massive companion galaxies since the flarings and radial increase of disk scale heights are thought to be general properties of tidally perturbed disks. According to the colors of the two clumps inside the diffuse region at the edge of the east disk, they seem to be sites of active star formation triggered by tidal forces from the companion galaxies.

• Journal of The Korean Astronomical Society
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• v.34 no.2
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• pp.59-66
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• 2001

In this paper, we investigate the correlation between the radial ultraviolet color distribution and the shapes of the ultraviolet isophote for elliptical galaxies (M32, NGC 1399) and spiral bulges (of M31, M81) by using their archival UIT images. For M31, M81, and NGC 1399, the radial ultraviolet color distributions show a two-component trend; as the distance from the galactic center increase the color becomes redder in the inner region while it becomes bluer in the outer region. On the other hand, the color of M32 continues to become bluer with the increasing galactocentric distance. We also find, unlike the optical/IR images, significant variations of the position angle and the ellipticity in the ultraviolet isophotes of M31, M81, and NGC 1399 through the inner regions. For M32, the variation is significant in the outer region. Since these variation implies the triaxiality of their intrinsic shapes, we suggest that the early-type galaxies and spiral bulges with a radial color gradient in ultraviolet tend to have a triaxiality. On the other hand, the shape parameter characterized by the fourth order cosine Fourier coefficient of the isophote, a(4)/a, indicates that the systematic deviations of the ultraviolet isophotes of the four galaxies are smaller than $\~0.2\%$ in units of the semi-major axis. The latter result implies that the ultraviolet isophotes of the galaxies have a pure elliptical shape rather than the boxy or disky shapes. Therefore, there is no clear evidence of correlation between the radial ultra-violet color gradient and the boxy/disky shapes of isophotes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.350-356
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• 2017

With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.