• ETRI Journal
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• v.32 no.5
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• pp.687-694
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• 2010

Breaks in presence (BIP) are those moments during virtual environment (VE) exposure in which participants become aware of their real world setting and their sense of presence in the VE becomes disrupted. In this study, we investigate participants' experience when they encounter technical anomalies during game play. We induced four technical anomalies and compared the BIP responses of a navigation mode game to that of a combat mode game. In our analysis, we applied a linear mixed model (LMM) and compared the results with those of a conventional regression model. Results indicate that participants felt varied levels of impact and recovery when experiencing the various technical anomalies. The impact of BIPs was clearly affected by the game mode, whereas recovery appears to be independent of game mode. The results obtained using the LMM did not differ significantly from those obtained using the general regression model; however, it was shown that treatment effects could be improved by consideration of random effects in the regression model.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1524-1524
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• 2001

A previous paper(Ito et al., 2000) has described the improvement of the standard error(SEC and SEP) of the predicted soluble solids(Brix) in a melon cultivar by non-contact mode with a fiber optic probe. Then we examined the immature and mature fruits. The objective of this study was to determine if non-contact mode could improve the standard error of the predicted Brix of matured melon fruits from cross progeny as well as the contact mode(usual method). The optical absorption spectrum was measured using a NIR Systems model 6500 spectrophotometer. A commercial spectral program(NSAS ver. 3.27) was used for multiple linear regression analysis. Absorbances of 902 and in the vicinity of 877 nm were included as the independent variables in both multiple regression equations. These wavelengths are key wavelengths for non-destructive Brix determination. When the results for the contact mode and non-contact mode are compared, the latter mode improved the former standard error(SEP and RMS).

• Korean Parent-Child Health Journal
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• v.13 no.2
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• pp.95-101
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• 2010

Purpose: This study is intended to identify difference postpartum depression according to delivery mode in the postpartum women. Methods: The subjects were 239 postpartum women in D and A city. Data collected from June 9, 2006 to August 6, 2007 using structured questionnaire surveys and convenience sampling. Measuring instrument was BDI (Beck Depression Inventory) translated By Lee and Song (1991). Collected data was analyzed by $x^2$-test, ANCOVA, Stepwise Multiple Regression with SPSS/PC 14.0. Results: There were significant differences in postpartum period ($x^2$=12.40, p = .002) and sleeping hours ($x^2$=9.09, p = .011) as analysed distribution of the subjects according to delivery mode. As result of analyzing the difference of postpartum depression according to delivery mode using ANCOVA, C-sec women's postpartum depression was higher than vaginal delivery women statistically (F=6.32, p = .013). As a result of Multiple Regression, income was a influencing factor of postpartum depression in vaginal delivery women and support of spouse and sleeping hours were influencing factors in C-sec women. Conclusion: There were differences in postpartum depression and their influencing factors according to delivery mode. Therefore it is necessary to develop and study a concrete nursing intervention and strategies for reducing the postpartum depression according to delivery mode.

• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.145-155
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• 2010

As the green transportation mode, revitalization of bike usage attracts remarkable public attention. For the acquirement of effective outcome, however, the concrete and close analysis about bike utilization characteristics should be arranged first. One result by MLTM(2009) is support this opinion; the bike mode share has been decreased whereas 9,170km of the bicycle path was improved(1995~2007). This study analyzed the bike mode share classified by trip types by using the 303,308 data of Household Travel Survey of Seoul Metropolitan Area, 2006. The highest mode share rate was induced by the institute attendee and Officetel resident as 3.75% and 3.13%, respectively. Also this study established the bike mode share estimation model of Seoul by logistic regression, and analyzed related factors and level of effectiveness related bike demand by calculation of odds ratio in terms of logistic regression coefficients. In conclusion, short trips, institutes district, parks, and Officetel residential area oriented policy should be effective on the revitalization of bike usage.

• Wind and Structures
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• v.38 no.5
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• pp.381-398
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• 2024

This study presents a mode analysis of 3D turbulent velocity data around a square-section building model to identify the dynamic system for Kármán-type vortex shedding. Proper orthogonal decomposition (POD) was first performed to extract the significant 3D modes. Magnitude-squared coherence was then applied to detect the phase consistency between the modes, which were roughly divided into three groups. Group 1 (modes 1-4) depicted the main vortex shedding on the wake of the building, with mode 2 being controlled by the inflow fluctuation. Group 2 exhibited complex wake vortexes and single-sided vortex phenomena, while Group 3 exhibited more complicated phenomena, including flow separation. Subsequently, a third-order polynomial regression model was used to fit the dynamics system of modes 1, 3, and 4, which revealed average trend of the state trajectory. The two limit cycles of the regression model depicted the two rotation directions of Kármán-type vortex. Furthermore, two characteristic periods were identified from the trajectory generated by the regression model, which indicates fast and slow motions of the wake vortex. This study provides valuable insights into 3D mode morphology and dynamics of Kármán-type vortex shedding that helps to improve design and efficiency of structures in turbulent flow.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.611-622
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• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.935-943
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• 2006

Key factors affecting the mode share of Soul metro are investigated. The log-regression model, which can describe the elasticity of the factors with ease, is established rather than the conventional mode choice model is used. The log-regression model requires lower level of data availability for calibration and identifies the impact of the factors on mode share straightforwardly. As a result, it is found that the main reasons why the current mode share of railway is low are due to several problems such as winding lines, inconvenient transfers and unnecessary bypasses. The calibrated model is adopted to evaluate the network reshuffling alternatives. The network reshuffling is to rearrange the existing inefficient railway lines that have frequent transfers and many winding segments. The proposed network reshuffling, which includes straightening winding lines and changing grade separated transfers into cross-platform transfers, turned out to be a good measure to tackle the problems.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.89.2-89.2
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• 2013

Solar energetic transients, e.g., flares, CMEs, etc., release large amount of energy which is expected to excite acoustic waves (p-modes) by exerting mechanical impulse of the thermal expansion of the flare on the photosphere. We study the p-mode properties of flaring and dormant active regions (ARs) to find association between flare and p-mode parameters. We compute the magnetic and flare activity indices of ARs using the line-of-sight magnetograms and GOES X-ray fluxes, respectively. The p-mode parameters are computed from the ring-diagram analysis. We correct p-mode parameters for magnetic field, filling factors and foreshortening by multiple linear-regression analysis. Our analysis of several flaring and dormant ARs observed during the Carrington rotations 1980-2109, showed strong association of mode parameters with magnetic and flare activities. We find that the mode parameters are contaminated by the geometrical effect. Mode amplitude decreases with angular distance from the solar disc centre. The mode width increases with magnetic activity while amplitude showed opposite relation due to mode absorption by the sunspot. After correcting modes due to all geometrical effects, magnetic activity and filling factor, we find that the modes amplitude, and mode energy increases with flare energy while width shows opposite relation.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.524-527
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• 2004

Hybrid rocket had many advantage with compared to solid and liquid rockets. However, the engines have not yet been used in practical rocket systems, due mainly to the disadvantage of hybrid combustion, such as low fuel regression rate. In this study, lab-scale hybrid motor was designed and manufactured. And the methods of regression rate improvement were considered. Test firings with thrusts up to 300 N were conducted with GOX and transparent PMMA. Thrust was calculated with the pressure of the combustion chamber and the regression rate was measured in with variation of oxidizer flow rate. The regression rates showed a strong dependency on GOX mass flux. The frequency analysis technique of the bulk-mode oscillation of motor was applied to a hybrid rocket motor and was based on the principle that this frequency was inversely proportional to the square root of the chamber volume. Several problems and solutions of operating hybrid rocket were presented.