• The Journal of Korean Academy of Sensory Integration
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• v.17 no.1
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• pp.19-29
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• 2019

Objective : The aim of this study was to verify validity of the Activity Participation Assessment for school-age children. Methods : A questionnaire consisting of 30 items from the APA, 75 items from the PACS, and 55 items from the CAPE was administered to elementary school students. A total of 207 questionnaires were analyzed. Confirmatory factor analysis was performed to confirm the construct validity of the APA. Convergence validity and discriminant validity were verified with the average variance extracted (AVE) and the square of the correlation coefficient. The discriminant validity was the Pearson correlation coefficient of the APA, PACS, and CAPE. Results : The results of the analysis were as follows: 1) For construct validity, the goodness of fit of the modified hierarchical second-order factor model was found to be appropriate (p < .001), 2) For convergent validity, the AVE was higher than .50 for all latent variables, 3) For discriminant validity, the AVE of the latent variable was greater than the square of the correlation coefficient (0.239), 4) For concurrent validity, the correlation between the total sum of the APA and PACS scores showed a positive correlation in all domains, and the correlation coefficient ranged from .303 to .647 at a statistically significant level (p < .01), 5) The correlation coefficient between the total sum of the APA and CAPE scores was .490 for recreational activities, .329 for physical activities, .571 for social activities, .401 for skill-based activities, and .390 for self-improvement activities. All domains showed a positive correlation, and were statistically significant (p < .01). Conclusion : APA can be used as a valid assessment tool to measure the participation of school aged children.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.187-196
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• 2011

Induction motors play a vital role in aeronautical and automotive industries so that many researchers have studied on developing a fault detection and classification system of an induction motor to minimize economical damage caused by its fault. With this reason, this paper extracts robust feature vectors from the normal/abnormal vibration signals of the induction motor in noise circumstance: partial autocorrelation (PARCOR) coefficient, log spectrum powers (LSP), cepstrum coefficients mean (CCM), and mel-frequency cepstrum coefficient (MFCC). Then, we classified different types of faults of the induction motor by using the extracted feature vectors as inputs of a neural network. To find optimal feature vectors, this paper evaluated classification performance with 2 to 20 different feature vectors. Experimental results showed that five to six features were good enough to give almost 100% classification accuracy except features by CCM. Furthermore, we considered that vibration signals could include noise components caused by surroundings. Thus, we added white Gaussian noise to original vibration signals, and then evaluated classification performance. The evaluation results yielded that LSP was the most robust in noise circumstance, then PARCOR and MFCC followed by LSP, respectively.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.157-169
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• 2016

We compare four methods to estimate a regression coefficient under linear regression models with serially correlated errors. We assume that regression errors are generated with nonlinear autoregressive models. The four methods are: ordinary least square estimator, general least square estimator, parametric regression error correction method, and nonparametric regression error correction method. We also discuss some properties of nonlinear autoregressive models by presenting numerical studies with typical examples. Our numerical study suggests that no method dominates; however, the nonparametric regression error correction method works quite well.

• Economic and Environmental Geology
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• v.37 no.4
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• pp.401-411
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• 2004

The Earth's total magnetic field was calculated from on board TAM(Three-Axis Magnetometer) observations of KOMPSAT-1 satellite between June 19th and 21st, 2000. The TAM's telemetry data were transformed from ECI(Earth-Centered Inertial Frame) to ECEF(Earth-Centered Earth-Fixed Frame) and then to spherical coordination. Self-induced field from the satellite bus were removed by the symmetric nature of the magnetic field. The 2-D wavenumber correlation filtering and quadrant-swapping method were applied to eliminate the dynamic components and track-line noise. To test the validity of the TAM's geomagnetic field, ${\phi}$rsted satellite's magnetic model and IGRF2000 model were used for statistical comparison. The correlation coefficients between KOMPSAT-1/${\phi}$rsted and KOMPSAT-1/IGRF2000 models are 0.97 and 0.96, respectively. The global spherical harmonic coeffi-cient was then calculated from the KOMPSAT-1 data degree and order of up to 19 and compared with those from IGRF2000, $\phi$rsted, and CHAMP models. The KOMPSAT-1 model was found to be stable to degree & order of up to 5 and it can give new information for the low frequency components of the global geomagtic field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.127-135
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• 2020

This study examined the effects of self-efficacy, standard precaution knowledge, and awareness on the performance of nursing students. Data collection was May 1-30, 2019, and the final 246 replies were used for analysis. The collected data were analyzed using the SPSS/WIN 22.0 program using descriptive statics and a t-test, ANOVA, Scheffe's test, Pearson correlation coefficient, and multiple regression analysis. The average self-efficacy score was 3.23±0.39. The overall standard precaution knowledge, average awareness, and average performance were 15.87±2.17, 4.63±0.46, and 4.73±0.32, respectively. The standard precaution performance, according to the general characteristics, was not significant. A positive correlation was observed between the standard precaution performance and self-efficacy (r=.266, p<.001) and awareness (r=.435, p<.001). Regression analysis showed a 21.3% variance in the nursing student's standard precaution performance with self-efficacy (β=.396, p<.001), awareness (β=.180, p=.002). A follow-up survey of the factors influencing nursing student's standard precaution performance and the development of a program will be required.

• International Area Studies Review
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• v.16 no.1
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• pp.275-301
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• 2012

This study analyzes the regional disparity in India between 24 states over the period 1980 to 2009. The traditional regressive and spatial autoregressive models are used that includes measures of spatial effects. The results provide no evidence that convergence is valid in India. However, the results indicate that spatial interaction is an important element of state growth in India. The result of spatial analysis excluded two outliner states reveals more strong relationship between the weighted spatial income level and the state growth rates. Moreover, the results find that the coefficients of spatial lag of initial per capital and error terms are significantly negative. The coefficient of variation measures that the distribution of state income level has diverged over time. Therefore, this study concludes that the growth of regional state income does not have a tendency to converge rater than diverge. The results is rational because as the Indian economy is growing rapidly, some states grow faster than the others while initial poor states become the poorest ones, which increases regional disparity in India.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.54-76
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• 1988

In Part Ⅰ of the paper, we have developed various block least mean-square (BLMS) adaptive digital filters (ADF's) based on a unified matrix treatment. In Part Ⅱ we analyze the convergence behaviors of the self-orthogonalizing frequency-domain BLMS (FBLMS) ADF and the unconstrained FBLMS (UFBLMS) ADF both for the overlap-save and overlap-add sectioning methods. We first show that, unlike the FBLMS ADF with a constant convergence factor, the convergence behavior of the self-orthogonalizing FBLMS ADF is governed by the same autocorrelation matrix as that of the UFBLMS ADF. We then show that the optimum solution of the UFBLMS ADF is the same as that of the constrained FBLMS ADF when the filter length is sufficiently long. The mean of the weight vector of the UFBLMS ADF is also shown to converge to the optimum Wiener weight vector under a proper condition. However, the steady-state mean-squared error(MSE) of the UFBLMS ADF turns out to be slightly worse than that of the constrained algorithm if the same convergence constant is used in both cases. On the other hand, when the filter length is not sufficiently long, while the constrained FBLMS ADF yields poor performance, the performance of the UFBLMS ADF can be improved to some extent by utilizing its extended filter-length capability. As for the self-orthogonalizing FBLMS ADF, we study how we can approximate the autocorrelation matrix by a diagonal matrix in the frequency domain. We also analyze the steady-state MSE's of the self-orthogonalizing FBLMS ADF's with and without the constant. Finally, we present various simulation results to verify our analytical results.

• Journal of the Korean Vacuum Society
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• v.9 no.3
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• pp.285-289
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• 2000

It has been well known that weak axial magnetic field on the process plasma enhances plasma density. As the magnetic field helps a specific polarized EM wave mode to penetrate into the plasma, the energy transfer to the plasma enhances and the ion density increases. We have analyzed systematic change of the dispersion relation caused by the cyclotron resonance condition. This resonance occurs at near 5 gauss to provide minimum penetration depth, as known before. RF penetration depth increases abruptly beyond the magnetic field of 5 gauss, and this phenomena lessen as the collision frequency increases.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.245-252
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• 2023

The purpose of this study was to investigate the effect of academic engagement, academic self-efficacy of problem solving ability in nursing students. Data were collected from 219 nursing students in B city and analyzed by descriptive statistics, t-test, ANOVA, Pearson correlation coefficient, and multiple regression using SPSS/WIN 22.0. The degree of problem solving ability in nursing students was 4.00±0.51. There were significant differences in problem solving ability with major satisfaction(F=9.476, p<.001), class satisfaction (F=3.079, p<.001). There was positive correlation between problem solving ability and academic engagement (r=.560, p<.001), academic self-efficacy(r=.634, p<.001). There was positive correlation between academic engagement and academic self-efficacy(r=.769, p<.001). The factors affecting problem solving ability of the study subjects were academic engagement(β=.177, p=.031), academic self-efficacy(β=.498, p<.001), with an explanatory power of 41.0%. Therefore to increase aacademic engagement and academic self-efficacy of nursing students, it is necessary to develop the program for improving the problem solving ability of nursing students.