• Journal of Korean Academy of Fundamentals of Nursing
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• v.13 no.2
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• pp.269-274
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• 2006

Purpose: This study was done to examine the level of performance and predictors influencing health promotion behavior of Korean students in China. Method: The participants were 160 Korean students who have lived in Beijing, China. Data were collected by self reporting questionnaire from september to november, 2001 and t-test, ANOVA, Person's correlation coefficients, and stepwise multiple regression were used to analyze the data. Results: The health promotion behavior score showed a positive correlation with perceived health status(r=.17, p=.025), social support(r=.29, p=.0001), and self-efficacy(r=.41, p=.0001). By use of stepwise multiple regression analysis, it was determined that the main factors influencing health promotion behavior were self-efficacy 17.0%(F=32.56, p=.0001) and social support 2.2%(F=4.11, p=.044). These variables explained 19.2% of the variance in the health promotion behavior scores. Conclusion: Self-efficacy and social support were the main factors influencing health promotion behavior. These findings showed that we need to develop nursing strategies to promote self-efficacy and social support for Korean students in China.

• Women's Health Nursing
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• v.30 no.2
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• pp.164-173
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• 2024

Purpose: This study aimed to investigate the prevalence of postpartum depression (PPD) and stress, as well as factors influencing PPD, among women in Saudi Arabia. Methods: This study employed a cross-sectional online survey and recruited participants during postpartum visits to the Clinic of Gynecology and Obstetrics in Al-Khobar, Saudi Arabia. Data collection was done using Arabic versions of the Edinburgh Postnatal Depression Scale, Perceived Stress Scale, and a sociodemographics and obstetric history questionnaire. Descriptive and inferential analyses were conducted, including multiple linear regression using a stepwise method. Results: Data from the 270 participants showed low levels of postpartum depressive symptoms with a mean score of 2.54±4.5 and low levels of perceived stress with a mean score of 2.49±6.2. While 94.4% of the participants reported low levels of stress and PPD, 5.6% reported elevated levels (≥10 for PPD, ≥14 for stress). The stepwise regression analysis showed significant results (p<.001), accounting for 34% of the variance in PPD. The factors significantly influencing PPD included the type of family, stress, number of abortions, disease during pregnancy, and family income. Importantly, perceived stress emerged as a factor influencing PPD. Conclusion: Although the majority of participants exhibited low levels of PPD, about 1 in 18 showed elevated levels. The identification of significant influencing factors highlights the need for targeted interventions to effectively address mental health concerns in postpartum women.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.30-37
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• 2008

Dynamic excitation and response analysis is an acceptable method to determine some of physical properties of agricultural product for quality evaluation. There is a difference in the internal viscoelasticity between sound and defective fruits due to the difference of geometric structures, thereby showing different vibration characteristics. This study was carried out to develop a portable piezoelectric film-based glove sensor system that can separate internally damaged watermelons from sound ones using an acoustic impulse response technique. Two piezoelectric sensors based on polyvinylidene fluoride (PVDF) films to measure an impact force and vibration response were separately mounted on each glove. Various signal parameters including number of peaks, energy ratio, standard deviation of peak to peak distance, zero-crossing rate, and integral value of peaks were examined to develop a regression-estimated model. When using SMLR (Stepwise Multiple Linear Regression) analysis in SAS, three parameters, i.e., zeros value, number of peaks, and standard deviation of peaks were selected as usable factors with a coefficient of determination ($r^2$) of 0.92 and a standard error of calibration (SEC) of 0.15. In the validation tests using twenty watermelon samples (sound 9, defective 11), the developed model provided good capability showing a classification accuracy of 95%.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.2
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• pp.172-175
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• 2003

The regression equations of dry weight of planktonic biomass upon physico-chemical characteristics of fifteen ponds in three replicates under the influence of artificial feed, broiler manure, buffalo manure, N:P:K (25:25:0) and a control pond was obtained after one year of experimental period by using stepwise regression method. Water samples from each of the ponds were analyzed daily. However, the average values were calculated on the basis of 15 day intervals designated as fortnight. In artificial feed supplemented pond the regression of average nitrates on dry weight of planktonic biomass accounted for 71.7% of the variation in biomass. In broiler manure fertilization pond the regression of total nitrogen on dry weight of planktonic biomass held it responsible for more than 74.6% of variation in biomass. In buffalo's manure fertilized pond more than 82% of the variations in biomass were due to total nitrogen. In case of N:P:K (25:25:0) treated pond 66% of the variation in the dry weight of planktonic biomass was due to average nitrates. The control pond showed the dependence of biomass on light penetration. This equation explained more than 62 percent of variation in biomass. Other variables also showed some contribution towards variation in biomass under all the treatments in these regression studies.

• Journal of the Korean Home Economics Association
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• v.28 no.1
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• pp.57-66
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• 1990

The purpose of this study was to investigate the analytical model of the implicit price according to objective and subjective characteristics of housing. The hedonic price regression was used for estimating the implicit price. The subjectives of this study were 1,143 dwellers who live in Seoul metropolitan area. Taejeon, and Jeonju. Satistical analyses were conducted using frequencies, percentiles, mean, and multiple regression. The major findings were as follows: 1. There was a significant difference in the implict price of the apartment between owners and renters. 2. There was a sginificant difference in the implicit price of the apartment among Seoul metropolitan area, Taejeon, and Jeonju. 3. Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between tenure types (owner/renter), and regions(Seoul metroplitan area/Taejeon/Jeonju). 4. The linear model was the most appropriate noe which explained the housing price. 5. Subjective characteristics of housing in Taejeon and Jeonju had an effect on the housing price more than those in Seoul metropolitan area.

• ETRI Journal
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• v.21 no.3
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• pp.6-15
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• 1999

Many studies in the software reliability have attempted to develop a model for predicting the faults of a software module because the application of good prediction models provides the optimal resource allocation during the development period. In this paper, we consider the change request data collected from the field test of the software module that incorporate a functional relation between the faults and some software metrics. To this end, we discuss the general aspect if regression method, the problem of multicollinearity and the measures of model evaluation. We consider four possible regression models including two stepwise regression models and two nonlinear models. Four developed models are evaluated with respect to the predictive quality.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.537-551
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• 2021

We conducted a study on a regression spline estimator with a few pre-specified auxiliary variables. For the implementation of the proposed estimators, we adapted a coordinate descent algorithm. This was implemented by considering a structure of the sum of the residuals squared objective function determined by the B-spline and the auxiliary coefficients. We also considered an efficient stepwise knot selection algorithm based on the Bayesian information criterion. This was to adaptively select smoothly functioning estimator data. Numerical studies using both simulated and real data sets were conducted to illustrate the proposed method's performance. An R software package psav is available.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2581-2588
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• 2000

In previous studies, the dynamic resistance, which was calculated by the process variables measured at the electrode of the welding machine, and the electrode displacement were used for quality exa mination. However, in-process usage of such systems is not effective in systems that include a welding gun attached to a robot. In order to overcome such problems, we obtained and used the process variables from the welding machine timer. This would allow us to estimate real time in -process weld quality. For quality estimation, the features were extracted as factors from the primary dynamic resistance patterns, which were measured in t he welding machine timer. The relationship between the indexes and nugget size of the welds was observed through the regression analysis. Using the analyzed factors, a regression model that could estimate nugget diameter was developed. Two regression equations of the model were suggested depending on the factors, and it was showed that the model developed by stepwise method was effective one for weld quality estimation. The developed estimation model was in good linearity with the nugget diameter obtained through the experimentation.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.155-165
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• 2022

As pork consumption increases, rapid and accurate determination of porcine carcass grades at abattoirs has become important. Non-destructive, automated inspection methods have improved slaughter efficiency in abattoirs. Furthermore, the development of a calibration equation suitable for non-destructive inspection of domestic pig breeds may lead to rapid determination of pig carcass and more objective pork grading judgement. In order to increase the efficiency of pig slaughter, the correct estimation of the automated-method that can accommodate the existing pig carcass judgement should be made. In this study, the previously developed calibration equation was verified to confirm whether the estimated traits accord with the actual measured traits of pig carcass. A total of 1,069,019 pigs, to which the developed calibration equation, was applied were used in the study and the optimal estimated regression equation for actual measured two traits (backfat thickness and hot carcass weight) was proposed using the estimated traits. The accuracy of backfat thickness and hot carcass weight traits in the estimated regression models through stepwise regression analysis was 0.840 (R²) and 0.980 (R²), respectively. By comparing the actually measured traits with the estimated traits, we proposed optimal estimated regression equation for the two measured traits, which we expect will be a cornerstone for the Korean porcine carcass grading system.