• Journal of Environmental Science International
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• v.11 no.1
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• pp.63-68
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• 2002

In this study, we examined statistical analysis between sewage plant operations parameters and effluent quality We got six components from principle component analysis of the operation parameters and secondary effluent quality. 91.8% of the total variance was explained by the six components. The components were identified in the following order : 1) organic matter removal by aeration basin microbe, 2) settleability on secondary clarifier load, 3) removal of nutrients, 4) microbial number increasement and species diversity, 5) microbial activity in aeration basin, 6) oxidation in aeration basin.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.2
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• pp.168-176
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• 2013

Purpose: The purpose of this study was to identify factors affecting quality of life according to Body Mass Index (BMI) of women college students. Methods: The research design was a descriptive survey design using a convenience sampling. Data were collected using self-report questionnaires. Participants were 348 women college students. Data analysis was done using SPSS/WIN 18.0 program for descriptive statistics, Pearson correlation coefficients and hierarchial multiple regression. Results: According to BMI, 3 groups of students were identified. Differences between the groups for quality of life were significant. The major factors affecting quality of life in the underweight group were departments (college), body stress and ego-resilience which explained 27.9% of the variance in quality of life. Body stress and ego-resilience were significant predictors explaining 23.1% of the variance in quality of life in the normal weight group. Ego-resilience was also a significant predictor in the overweight group explaining 15.2% of the variance in quality of life. Conclusion: Findings indicate a need to decrease body stress and strengthen ego-resilience to improve quality of life of women college students. Further studies are needed to examine nursing intervention strategies for improving quality of life for women college students.

• Journal of Korean Critical Care Nursing
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• v.15 no.3
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• pp.23-36
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• 2022

Purpose : This study aimed to identify the factors influencing the professional quality of life of intensive care unit (ICU) nurses working in university hospitals. Methods : A survey was conducted on 171 ICU nurses in university hospitals in B City, South Korea. This study used the Professional Quality of Life instrument, which consists of three subscales, namely, compassion satisfaction, burnout, and secondary traumatic stress. Data were analyzed using stepwise multiple regression analysis. Results : Compassion satisfaction was influenced by resilience, ICU job satisfaction, and innovation-oriented culture, and these variables explained 37.1% of the variance in compassion satisfaction. Burnout was influenced by resilience, a hierarchy-oriented culture, and ICU job satisfaction, and these variables explained 42.9% of the variance in burnout. Secondary traumatic stress was influenced by a task-oriented culture and resilience, and these variables explained 12.5% of the variance in secondary traumatic stress. Conclusion : These findings suggest the importance of improving resilience and job satisfaction to enhance the professional quality of life in ICU nurses. Moreover, creating an innovation-oriented culture rather than a hierarchical and task-oriented culture can effectively improve the professional quality of life of ICU nurses.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.7
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• pp.923-927
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• 2008

The objective of this study was to compare random regression model and multiple trait animal model estimates of the (co) variance of total sperm cells over the active lifetime of AI boars. Data were provided by Smithfield Premium Genetics (Rose Hill, NC). Total number of records and animals for the random regression model were 19,629 and 1,736, respectively. Data for multiple trait animal model analyses were edited to include only records produced at 9, 12, 15, 18, 21, 24, and 27 months of age. For the multiple trait method estimates of genetic and residual variance for total sperm cells were heterogeneous among age classifications. When comparing multiple trait method to random regression, heritability estimates were similar except for total sperm cells at 24 months of age. The multiple trait method also resulted in higher estimates of heritability of total sperm cells at every age when compared to random regression results. Random regression analysis provided more detail with regard to changes of variance components with age. Random regression methods are the most appropriate to analyze semen traits as they are longitudinal data measured over the lifetime of boars.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.5
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• pp.13-25
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• 2024

With the increasing wildfire damage driven by climate change, it is crucial to assess the effectiveness of restoration efforts on a large scale. The majority of forests in Korea are situated in rugged mountainous regions, making it challenging to monitor large-scale wildfires. Consequently, establishing methodologies that use satellite imagery to evaluate restoration effectiveness is essential. This study aims to assess the recovery trends of ecosystems in wildfire-affected areas using NDVI mean-variance plots, which monitor changes in NDVI mean and variance over time through satellite imagery and visually represent the restoration process. The analysis of NDVI mean-variance plots for different restoration methods revealed that landscape restoration had the slowest recovery. This slower recovery is likely due to reduced growth from the complete removal of damaged trees. In contrast to High Severity (HS) areas, Moderate High Severity (MHS) areas showed that commercial afforestation, revegetation, ecological forest treatment led to a more stable recovery state post-disturbance, suggesting that areas with lower wildfire severity may recover more quickly. Furthermore, the recovery trends between artificial and natural restoration showed no significant difference, indicating that natural restoration can have similar restoration effects to artificial restoration in appropriate areas. Therefore, the study emphasizes the need to expand natural restoration areas, considering ecological and economic benefits such as increased biodiversity and genetic resource conservation. This research provides critical baseline data for the formulation and implementation of restoration policies in large-scale wildfire-affected regions and is expected to contribute significantly to the development of effective management strategies and monitoring techniques.

• Journal of Korean Academy of Nursing
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• v.28 no.3
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• pp.625-637
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• 1998

To determine factors affecting self-care behavior of diabetics, the relationships of hardiness, family support, demographic and medical variables to self-care behavior were investigated in 180 samples with non-insulin dependent diabetes mellitus. In stepwise multiple regression analysis, 26.76% of the variance in self-care behavior was accounted for by family support(15.52%), age(7.76%), and clinical history (2.07%). To compare the magnitude of predictor's significance by gender, stepwise multiple regression was conducted seperatively by gender group. In the male sample 25.22% of the variance in self-care behavior was accounted for by family support, age, and challenge. In the female sample family support, age, and committment were significant predictors in self-care behavior with 28.82% of the variance. The results highlight the value of family support in self-care behavior in diabetics regardless of gender difference. According to the finding of this study, family support is the most significant predictor of self-care behavior in NIDDM. This implicates that in future diabetic care, a family member should be encouraged to participate in the patient education process. Also as hardiness is not supported by a unidimensional construct, more empirical studies are recommended to differentiate the conceptual traits for the three subconcepts of hardiness.

• Atmosphere
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• v.18 no.4
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• pp.475-483
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• 2008

The hourly precipitation data from 1973 to 2007 observed at 60 weather stations over Korea are used to characterize the diurnal and semidiurnal cycles of total precipitation amount, intensity and frequency and examine their spatial patterns and interannual variations. The results show that the diurnal cycle peaks in the morning (03-09LST) and the semidiurnal cycle peaks in the late afternoon (16-20LST). It is found that the spatial variations of the peak phase of diurnal or semidiurnal cycle relative to their corresponding seasonal mean cycle are considerably small (large) for total precipitation amount and intensity (frequency, respectively) in both winter and summer seasons. Also, the diurnal phase variations for individual years relative to the seasonal mean precipitation show the significant interannual variability with dominant periods of 2-5 years for all three elements of precipitation and the slightly decreasing trend in total precipitation amount and intensity. To compare the relative contributions of frequency and intensity to the diurnal and semidiurnal cycles (and their sum) of total precipitation amount, the percentage variance of each cycle of precipitation amount explained by frequency is estimated. The fractional variance accounted for by precipitation intensity is greater than that of frequency for these three cycles. All above analyses suggest that intensity plays a more important role than frequency in the diurnal variations of total precipitation amount.

• Korean journal of food and cookery science
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• v.19 no.6
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• pp.745-752
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• 2003

The aim of this study was to test the behavioral intent-based model of the foodservice related complaint handling. Accordingly, this study examined the effects of complaint handling on the university students' behaviort based on the word-of-mouth intent and repurchase intent. The findings from this study were as follows. KMO and Bartlett's test statistics showed the data fit factor analysis. The factor loadings, eigenvalues, ％ of variance, and communalities showed that the convergent validity was supported, the average variance extracted estimates and shared variance showed that the discriminant validity is supported, and composite alpha showed that the internal consistency was supported. It was found that some of main effects on the word-of-mouth intent and the repurchase intent were significant. It was found that some of interactional effects of the complaint type, the degree of correction effort, and the satisfaction with the complaint handling were significant. Overall, the results provide some insights into the types of foodservice related complaint handling strategies or the tactics that can be effectively employed by operators who manage complaint handling for customers dining at fast food restaurants.

• The Mathematical Education
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• v.45 no.2 s.113
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• pp.145-154
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• 2006

The main purpose of this study is to investigate the effect of departures from normality and equal variance on the two-sample test when the variances are unknown. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. But the change of type I error was mainly based on the skewness of the parent population. In introductory statistics classes where data analysis includes techniques for detecting skewness of two populations, we recommend the two-sample t-test when maximal skewness of two populations is smalter than the value 4 when the variances seem equal. Furthermore, our simulations reveal that the two-sample t-test appears somewhat more robust than that of z-test if the assumption of equal variance is satisfied. In the case of unequal variance, the two-sample t-test appears somewhat more robust provided the t-statistic using Satterthwaite's approximate degrees of freedom.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.