• Korean Journal of Mathematics
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• v.22 no.4
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• pp.671-681
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• 2014

In this paper, we consider general Beta operators, which is a general sequence of integral type operators including Beta function. We study the King type Beta operators which preserves the third test function $x^2$. We obtain some approximation properties, which include rate of convergence and statistical convergence. Finally, we show how to reach best estimation by these operators.

• Asia-Pacific Journal of Business
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• v.10 no.1
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• pp.1-11
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• 2019

Asian countries have been striving for economic integration for decades. This effort may lead to the convergence of income level through externalities across countries. This paper investigates whether the convergence phenomenon holds for income levels in Asian countries for the periods between 1975-2015 applying the traditional methodology of ${\sigma}-$ and ${\beta}-convergence$. Although the absolute ${\beta}-convergence$ of income levels in Asian and ASEAN+3 countries do hold, ${\sigma}-convergence$ and conditional ${\beta}-convergence$ of income level generally do not exist. This suggests that the benefits of economic integration in Asian countries were not yet realized to be significant. A plausible explanation is that the economies of Asian countries are largely based on low trade openness and a high level of informal economy.

• Journal of the Korean Geographical Society
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• v.39 no.2
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• pp.212-228
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• 2004

This paper is concerned with an important aspect of regional income convergence, ${\beta}$-convergence, which refers to the negative relationship between initial income levels and income growth rates of regions over a period of time. The common research framework on ${\beta}$-convergence which is based on OLS regression models has two drawbacks. First, it ignores spatially autocorrelated residuals. Second, it does not provide any way of exploring spatial heterogeneity across regions in terms of ${\beta}$-convergence. Given that empirical studies on ${\beta}$-convergence need to be edified by spatial data analysis, this paper aims to: (1) provide a critical review of empirical studies on ${\beta}$-convergence from a spatial perspective; (2) investigate spatio-temporal income dynamics across the U.S. labor market areas for the last 30 years (1969-1999) by fitting spatial regression models and applying bivariate ESDA techniques. The major findings are as follows. First, the hypothesis of ${\beta}$-convergence was only partially evidenced, and the trend substantively varied across sub-periods. Second, a SAR model indicated that ${\beta}$-coefficient for the entire period was not significant at the 99％ confidence level, which may lead to a conclusion that there is no statistical evidence of regional income convergence in the US over the last three decades. Third, the results from bivariate ESDA techniques and a GWR model report that there was a substantive level of spatial heterogeneity in the catch-up process, and suggested possible spatial regimes. It was also observed that the sub-periods showed a substantial level of spatio-temporal heterogeneity in ${\beta}$-convergence: the catch-up scenario in a spatial sense was least pronounced during the 1980s.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.89-99
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• 2017

This study was to identify the convergence factors that affect work engagement in medium and small hospitals nurses, The research method were self -report questionnaire was completed by 198 nurse three hospitals in B city between April 18th to April 30th, 2016. and date analyzed using the IBM SPSS/WIN 22.0 program. As a result, work engagement was positively correlated with psychological capital and psychological well-being, significantly affecting Convergence Factors analysis showed that with positive psychological capital(${\beta}=.363$, p<.001) and psychological well-being(${\beta}=.300$, p<.001) explained 52.7%, level of education(${\beta}=.102$, p=.040), job satisfaction(${\beta}=.109$, p=.044), nursing satisfaction(${\beta}=.137$, p=.022) explained 4.4% of the work engagement. Based on this, It is necessary to develop and verify program to enhance the positive psychological capital and psychological well-being of medium small hospital nurses.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.120-127
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• 2019

A study on the factors affecting oral health beliefs of some high school third graders on oral health promotion behavior After the oral health education on November 21, 2017, 160 students who explained and agreed on the study purpose and method were final analyzed. Oral health belief and oral health promotion behavior according to general characteristics were analyzed with t-test, one-way ANOVA, and the correlation with Pearson's correlation test. The convergence factors affecting oral health promotion were performed multiple regression analysis. The convergence factors affecting oral health promotion were performed multiple regression analysis. Oral health belief was the highest with 3.61 points, with 4.06 points of benefit, while oral health promotion with 3.25 points. Convergence factors affecting oral health improvement were shown as susceptibility (${\beta}=-0.210$), salienece(${\beta}=0.396$), seriousness(${\beta}=0.306$), and barrier(${\beta}=-0.170$). To explore ways to change the oral health beliefs of high school students, the school district health education is very important, and various oral health education programs to promote oral health promotion should be developed.

• Journal of Sensor Science and Technology
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• v.21 no.5
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• pp.319-323
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• 2012

In this paper, we present the possibility of quantification analysis for $A{\beta}$ captured by micro beads using Near-filed detection. In order to evaluate detection efficiency, detected signals were compared with different sizes of micro beads and a varied number of micro beads. Also, $A{\beta}$ deposits and $A{\beta}$ binding to micro beads were measured, therefore, we observed the $A{\beta}$ deposit and light scattering around the surface of micro beads induced by attached $A{\beta}$. This method can be used for quantitative analysis for not only the number of $A{\beta}$, but also the binding ratio of $A{\beta}$ to micro beads.

• Mycobiology
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• v.43 no.1
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• pp.57-62
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• 2015

${\beta}$-Glucosidase, which hydrolyzes cellobiose into two glucoses, plays an important role in the process of saccharification of the lignocellulosic biomass. In this study, we optimized the activity of ${\beta}$-glucosidase of brown-rot fungus Fomitopsis pinicola KCTC 6208 using the response surface methodology (RSM) with various concentrations of glucose, yeast extract and ascorbic acid, which are the most significant nutrients for activity of ${\beta}$-glucosidase. The highest activity of ${\beta}$-glucosidase was achieved 3.02% of glucose, 4.35% of yeast extract, and 7.41% ascorbic acid where ascorbic acid was most effective. The maximum activity of ${\beta}$-glucosidase predicted by the RSM was 15.34 U/mg, which was similar to the experimental value 14.90 U/mg at the 16th day of incubation. This optimized activity of ${\beta}$-glucosidase was 23.6 times higher than the preliminary activity value, 0.63 U/mg, and was also much higher than previous values reported in other fungi strains. Therefore, a simplified medium supplemented with a cheap vitamin source, such as ascorbic acid, could be a cost effective mean of increasing ${\beta}$-glucosidase activity.

• East Asian mathematical journal
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• v.22 no.1
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• pp.79-91
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• 2006

In this paper, we will show some relations between decomposition series {$\pi^{\alpha}q\;:\;{\alpha}$ is an ordinal} and topological series {$\tau_{\alpha}q\;:\;{\alpha}$ is an ordinal} for a convergence structure q and the formular ${\pi}^{\beta}(\tau_{\alpha}q)={\pi}^{{\omega^{\alpha}\beta}}q$, where $\omega$ is the first limit ordinal and $\alpha$ and $\beta({\geq}1)$ are ordinals.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.79-85
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• 2019

The purpose of this study was to investigate the convergence relationship between the clinical practice stress and professional identity of 171 dental hygiene students from 3 university in Jeollanam-do area. The data were analyzed using SPSS WIN 18.0 program. Professional identity was negatively correlated with clinical practice training environment(r=-0.352, p<0.01), clinical practice work burden(r=-0.185, p<0.05) and conflicts with patients(r=-0.181, p<0.05). The convergence factors influencing professional identity were clinical practice training environment(${\beta}=-0.261$), aptitude(${\beta}=0.238$), advice from others(${\beta}=-0.186$) and clinical practice unsatisfied(${\beta}=-0.176$). The regression model explained 23.7% of professional identity. Therefore, it is necessary to develop a program for the smooth labor supply by understanding the relationship between clinical practice stress and professional identity in dental hygiene students.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.