• The Journal of Korean Academy of Prosthodontics
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• v.49 no.2
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• pp.101-105
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• 2011

The purpose of this study was to assess the marginal fit of three-unit bridges produced using LAVA CAD/CAM (computer-aided design/computer-aided manufacturing) system and conventional PFG in vitro. Materials and methods: #11, 13 resin teeth were prepared on dentiform, then duplicated. Twenty resin models were fabricated, ten for PFG 3-unit bridges and ten for LAVA 3-unit bridges. Each bridge was cemented on the resin model. Marginal discrepancy was measured with stereoscopic microscope (Nikon DS-Fi 1, Nikon, Japan) at a magnification of ${\times}75$. Independent t-test was done for the statistical analysis. Results: The mean marginal discrepancy values and standard deviations of the PFG bridges was $97.1{\pm}18.7\;{\mu}m$ for incisors, $76.6{\pm}21.8\;{\mu}m$ for canines; that of the LAVA bridges was $90.4{\pm}26.7\;{\mu}m$ for incisor, $110.2{\pm}30.2\;{\mu}m$ for canines. The mean marginal discrepancy between PFG and LAVA for incisor did not show significant difference (P<.05). But for canine, the mean marginal discrepancy of PFG bridges was smaller than that of LAVA bridges (P<.05). Conclusion: The LAVA CAD/CAM 3-unit bridges and the PFG 3-unit bridges showed clinically acceptable marginal discrepancy.

• Food Science and Preservation
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• v.22 no.5
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• pp.683-689
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• 2015

Response surface methodology (RSM) is a statistical procedure frequently used for optimization studies. The purpose of this study was to determine the optimal spray drying condition for manufacturing Sikhye powder using RSM. Independent variables included the additive contents of maltodextrin (MD), inlet temperature, and velocity of sample feed velocity. The dependent variables were water uptake (g), solubility (%) and particle size (${\mu}m$). Regression models describing the changes of water uptake (g), solubility (%) and particle size (${\mu}m$) with respect to the independent variables were statistically significant with coefficients of determination, $R^2$, greater than 0.9. The results indicated that the inlet temperature of the spray dryer was the most important independent variable that affected the water uptake (g), while the additive content of MD and the sample feed velocity had maximum effects on the solubility (%) and particle size (${\mu}m$) of the Sikhye powder, respectively. The optimum final product was expected to have the lowest possible water uptake (g) and particle size (${\mu}m$) but the highest possible solubility (%). In conclusion, the best spray drying conditions were as follows: additive MD content, 22%; inlet temperature, $140^{\circ}C$ ; and spray dryer sample feed velocity, 51 mL/min.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.929-938
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• 2020

In this study, we estimated missing evapotranspiration (ET) data at a eddy-covariance flux tower in the Cheongmicheon farmland site using the Artificial Neural Network (ANN). The ANN showed excellent performance in numerical analysis and is expanding in various fields. To evaluate the performance the ANN-based gap-filling, ET was calculated using the existing gap-filling methods of Mean Diagnostic Variation (MDV) and Food and Aggregation Organization Penman-Monteith (FAO-PM). Then ET was evaluated by time series method and statistical analysis (coefficient of determination, index of agreement (IOA), root mean squared error (RMSE) and mean absolute error (MAE). For the validation of each gap-filling model, we used 30 minutes of data in 2015. Of the 121 missing values, the ANN method showed the best performance by supplementing 70, 53 and 84 missing values, respectively, in the order of MDV, FAO-PM, and ANN methods. Analysis of the coefficient of determination (MDV, FAO-PM, and ANN methods followed by 0.673, 0.784, and 0.841, respectively.) and the IOA (The MDV, FAO-PM, and ANN methods followed by 0.899, 0.890, and 0.951 respectively.) indicated that, all three methods were highly correlated and considered to be fully utilized, and among them, ANN models showed the highest performance and suitability. Based on this study, it could be used more appropriately in the study of gap-filling method of flux tower data using machine learning method.

• Research in Community and Public Health Nursing
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• v.11 no.2
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• pp.333-346
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• 2000

The purpose of this study was designed to test and develope the structural model that explains health promoting behaviors among college students in Korea. The hypothetical model was constructed on the Pender's Health promotion Model(l996) and the inclusion of some influential factors for life satisfaction. The conceptual framework was built around eight constructs. Exogenous variables included in the model were self-esteem, perceived health status, self-efficacy, internal locus of control, chance locus of control. powerful other locus of control. Endogenous variables were health promotion behaviors and life satisfaction. The results are as follows; 1. The overall fit of the hypothetical model to the data was moderate <$x^2$=4.18(df=11. p=0.041), GFI= 0.99, AGFI= 0.76, RMR= 0.019, CFI= 0.99, CN= 248.50> 2. Path and variable of the model were modified by considering both its theoretical implication and statistical significance of parameter estimates. Compared to the hypothetical model. the revised model has become parsimonious and had a better fit to the data expected in a chi-square value <$x^2$=8.43( df= 16, p=0.21), GFI= 0.99, AGFI= 0.92., RMR= 0.024, CFI= 0.99, CN= 312.01> 3. Some of the predictive factors. especially self efficacy. self esteem. powerful others locus of control. perceived health status revealed the direct effects on health promoting behaviors. Of these variables. self-efficacy was the most signigicant factor. These predictive variables of health promoting behaviors explained 59% of total variances in the model. 4. Health promoting behaviors, self-esteem. and perceived health status revealed direct effect on the life satisfaction. Self-efficacy was identified as an important variable that contributed indirectly to improve life satisfaction by enhancing health promoting behaviors. These predictive variables of life satisfaction explained 42% of total variances in the model. In conclusion. the derived model in this study is considered appropriate in explaining and predicting health promoting models and life satisfaction among college students in Korea and could effectively be used as a reference model for further studies by suggesting a direction in health promoting nursing practices.

• Research in Community and Public Health Nursing
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• v.14 no.3
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• pp.375-384
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• 2003

The purpose of this study is to identify the amount of social support and quality of life perceived by elderly people in rural areas and to examine the relationship between social support and quality of life in an effort to provide the basic data for effective nursing intervention to enhance quality of life among elderly people. Data were collected from a sample of 220 elderly people aged over 60 from a stratified probability method from one rural area in South Jeolla province from Aug. 15 to Sep. 15, 2002. For data collection, pre-educated researchers visited the participants' homes and surveyed them face-to-face. The statistical analysis was performed using the SAS program along with t-test, ANOVA, and Pearson Correlation. The findings were as follows: 1. The most socially supportive people they answered were Spouses (57.28%), followed by children, friends/neighbors, in descending order. In terms of satisfaction about social support, the subjects felt the most satisfaction from spouses, followed by friends/neighbors, children, in descending order. 2. The participants' perceived social support was 26.0 and the highest score was 108.0 out of 125. Also, the average score and average grade point was 81.7 and 3.35, respectively. A comparison of the average grade points per items within sub-areas of social support revealed financial aid(3.56), informative support(3.34), emotional support (3.27), and evaluation support(3.22). 3. Their perceived social support had statistically significant differences in terms of how much they earned (F=18.56, p= .00001) and whether they had family members living together (F=2.68, p= .0512), quality of life had statistically significant differences in terms of how much they earned (F=35.34, p= 0.00001). 4. The quality of life they perceived was the lowest score 47.0, the highest score 196.0, average score 145.7, and average grade points 3.28. A comparison of the average grade points per items within sub-areas of quality of life revealed neighbor relationships(3.97), self-esteem(3.49), family relationships(3.35), economic conditions 3.12), physical health (2.98), and psychological health(2.74). 5. The relationship between the amount of the subjects' social support and quality of life was significantly correlated (r=.696, p< .001). The findings revealed that social support for elderly people in rural areas was a greatly effective factor on their quality, of life. Also, it was shown that the larger the social support for the elderly, the greater the quality of life for them. Therefore, it is necessary to foster geriatric nurse specialists and develop nursing intervention programs connected with health care and social wellbeing in order to enhance the quality of life of elderly people in rural areas. Also, it is necessary to develop effective models for community and its applications, which will playa leading role for elderly people.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11B
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• pp.1501-1509
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• 2001

Recently, the use of wireless communication systems has been rapidly increasing, which results in a difficult problem in efficient control of limited frequency resources. As a way of solving this problem, the ultra wideband time hopping impulse radio system attracts much attention. The impulse radio system communicates pulse position modulated data using Gaussian monocycle pulses of very short duration less than 1 nsec. Thus the transmitted signal has very low power spectral density and ultra wide bandwidth from near D.C. to a few GHz. It is blown that it hardly interferes with the existing communication systems because of its very low power spectral density. The purpose of this paper is to characterize multipath propagation of the impulse radio signal and to evaluate the performance of the correlator-based receiver for the multipath environments. In this paper, we consider the deterministic two-path model and the statistical indoor multipath model of Saleh and Valenzuela. For the two-path model the output of the correlator with the ideal reference waveform varies according to the relative difference between the indirect path delay and the time interval of PPM, and to the indirect path gains. In addition, the characteristics of bit error rates is measured for the two models through computer simulation. The simulation results indicate that the performance of the impulse radio system depends both on the relative difference between the indirect path delay and the time interval of PPM, and on the indirect path gains. Furthermore, it is observed that the reference signal designed for the AWGN channel can not be applied to the multipath channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1422-1432
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• 1993

Nonlinear mapping function of the HCNN( Hidden Control Neural Network ) can change over time to model the temporal variability of a speech signal by combining the nonlinear prediction of conventional neural networks with the segmentation capability of HMM. We have two things in this paper. first, we showed that the performance of the HCNN is better than that of HMM. Second, the HCNN with its prediction error measure given by weighted distance is proposed to use suitable distance measure for the HCNN, and then we showed that the superiority of the proposed system for speaker-independent speech recognition tasks. Weighted distance considers the differences between the variances of each component of the feature vector extraced from the speech data. Speaker-independent Korean digit recognition experiment showed that the recognition rate of 95%was obtained for the HCNN with Euclidean distance. This result is 1.28% higher than HMM, and shows that the HCNN which models the dynamical system is superior to HMM which is based on the statistical restrictions. And we obtained 97.35% for the HCNN with weighted distance, which is 2.35% better than the HCNN with Euclidean distance. The reason why the HCNN with weighted distance shows better performance is as follows : it reduces the variations of the recognition error rate over different speakers by increasing the recognition rate for the speakers who have many misclassified utterances. So we can conclude that the HCNN with weighted distance is more suit-able for speaker-independent speech recognition tasks.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.811-822
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• 2005

Automated text categorization is to classify free text documents into predefined categories automatically and whose main goals is to reduce considerable manual process required to the task. The researches to improving the text categorization performance(efficiency) in recent years, focused on enhancing existing classification models and algorithms itself, but, whose range had been limited by feature based statistical methodology. In this paper, we propose RTPost system of different style from i.ny traditional method, which takes fault tolerant system approach and data mining strategy. The 2 important parts of RTPost system are reinforcement training and post-processing part. First, the main point of training method deals with the problem of defining category to be classified before selecting training sample documents. And post-processing method deals with the problem of assigning category, not performance of classification algorithms. In experiments, we applied our system to documents getting low classification accuracy which were laid on a decision boundary nearby. Through the experiments, we shows that our system has high accuracy and stability in actual conditions. It wholly did not depend on some variables which are important influence to classification power such as number of training documents, selection problem and performance of classification algorithms. In addition, we can expect self learning effect which decrease the training cost and increase the training power with employing active learning advantage.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.3
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• pp.258-264
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• 2011

A MCS technique is represented to stochastically analyze the uncertainties of wave forces exerted on the upright sections of composite breakwaters. A stochastical models for horizontal and uplift wave forces can be straightforwardly formulated as a function of the probabilistic characteristics of maximum wave height. Under the assumption of wave forces followed by extreme distribution, the behaviors of relative wave forces to Goda's wave forces are studied by the MCS technique. Double-truncated normal distribution is applied to take the effects of uncertainties of scale and shape parameters of extreme distribution into account properly. Averages and variances of relative wave forces are quantitatively calculated with respect to the exceedance probabilities of maximum design wave height. It is found that the averages of relative wave forces may be decreased consistently with the increases of the exceedance probabilities. In particular, the averages on uplift wave force are evaluated slightly larger than those on horizontal wave force, but the variations of coefficient of the former are adversely smaller than those of the latter. It means that the uncertainties of uplift wave forces are smaller than those of horizontal wave forces in the same condition of the exceedance probabilities. Therefore, the present results could be useful to the reliability based-design method that require the statistical properties about the uncertainties of wave forces.

• The Korean Journal of Pesticide Science
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• v.6 no.3
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• pp.209-217
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• 2002

Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.