• Korean Journal of Child Studies
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• v.35 no.2
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• pp.1-23
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• 2014

The purpose of this research was to investigate the most critical variables in the school adjustment of youth. In addition, this research assessed the impact of variables according to the categorization of individual, family, and school domains. To acquire the effect sizes, published studies between 1990 and 2012 were reviewed systematically and synthesized by meta-analysis. The major findings were as follows. First, this study identified a total of 34 variables which can have an influence on the school adjustment of youth and confirmed that 24 of those variables are significant. The most crucial variable that can influence school adjustment is that of a teacher's support. The next most important variables are self-resilience, relationships with friends, and self-efficiency. Focusing on the categorized elements, self-resilience is the most critical variable in the individual domain, the parent-child relation is the most crucial variable in the family domain, and a teacher's support is the most powerful variable in the school domain. Based on these results, this study suggested a number of the indispensable components in interventions to improve the youth's adjustment in school.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1153-1164
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• 2008

The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Uijeongbu monitoring site in Korea. The result showed that both overall and monthly ARE models are suited for describing the ozone concentration. In the ARE model, seven meteorological variables and four pollution variables are used as the as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide(SO2), Nitrogen dioxide(NO2), Cobalt(CO), and Promethium 10(PM10). Also, the high level ozone data (over 80ppb) have been analyzed four ARE models, General ARE, HL ARE, PM10 add ARE, Temperature add ARE model. The result shows that the General ARE, HL ARE, and PM10 add ARE models are suited for describing the high level of ozone data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1117-1124
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• 2010

The PM10 (Promethium 10) data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model has been considered for analyzing the monthly PM10 data at the southern part of the Gyeonggi-Do, Suwon monitoring site in Korea. In the ARE model, six meteorological variables and four pollution variables are used as the explanatory variables for the PM10 data set. The six meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, radiation, and amount of cloud. The four air pollution explanatory variables are sulfur dioxide ($SO_2$), nitrogen dioxide ($NO_2$), carbon monoxide (CO), and ozone ($O_3$). The result showed that the monthly ARE models explained about 13-49% for describing the PM10 concentration.

• Journal of Korean Academy of Nursing
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• v.37 no.5
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• pp.715-723
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• 2007

Purpose: The purposes of this study were 1) to compare the contribution of demographic-behavioral variables and psychological variables in explaining the variance of depression, 2) identify the most important predictors of depression for Korean female adolescents. Method: The participants were 840 female adolescents. Data was collected through self-report questionnaires, which were constructed to include demographic-behavioral factors, self-esteem, hostility, hopelessness, and depression. Data was analyzed using the SPSS program. Result: Female adolescents' demographic-behavioral variables explained 17% of the variance in depression, and perceived physical health status, history of physical abuse, smoking, satisfaction of body weight, parental alcohol abuse, parental divorce, and history of suicidal attempt were the significant predictors of depression for female adolescents. Psychological variables explained 50% of the variance in depression, and self-esteem, hostility, and hopelessness were the significant predictors of depression for female adolescents. The significant predictors of depression among female adolescents' demographic-behavioral variables and psychological variables were self-esteem, hostility, hopelessness, perceived physical health status, parental alcohol problem, and history of physical abuse, explaining 52% of the variance in depression. Conclusion: In order to reduce depression in female adolescents, it is necessary to design an intervention program that emphasizes improving self-esteem while reducing hostility and hopelessness.

• Journal of Forest and Environmental Science
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• v.35 no.1
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• pp.1-5
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• 2019

Species diversity is one of the most important indices that used to evaluate the sustainability of forest communities. In the present study, three variables including number of individuals (frequency of species), basal area and volume of tree species were compared to estimate tree species diversity in broadleaves forests of Iran. Based on systematic random design, 30 plots (circle plot, $1000m^2$) was selected. Type of species, number of species, DBH and height of trees were measured. Simpson (1-D), Hill ($N_2$), Shannon-Wiener (H'), Mc Arthur ($N_1$), Smith-Wilson ($E_{var}$) and Margalef ($R_1$) indices used to estimate tree species diversity. Species diversity was calculated in each plot. ANOVA test showed that there was a significant difference between of three variables used for estimation of species diversity. Number of trees variable has more precision than basal area and volume variables to estimate of species diversity. But Duncan test revealed that there were significant difference between of basal area and volume variables with number of trees. Therefore, basal area and volume variables were selected as more suitable variables in order to estimate of biodiversity indices in northern forests of Iran.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.924-935
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• 2023

Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.81-93
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• 2015

Objectives : The objective of this study was to examine preceding variables that affect the dual commitment of outsourced employees working at hospitals and to analyze the influence of these variables on job performance. Methods : Data were collected from 461 outsourced employees, working at 7 general hospitals, which had introduced the outsourcing system, using a structured, self-administered questionnaires. Frequency, validity/reliability, correlation and path analyses were done for data analysis. Results : The results of the path analyses showed that both commitment to the hiring company and commitment to the client company (hospital) had statistically significant positive effects on job performance. Additionally, when the 'single measurement' approach was used, dual commitment had a larger positive effect, compared with the 'parallel approach.' Among the preceding variables, 'satisfaction for the job itself' was found to be the most important variable affecting dual commitment and job performance. Conclusions : In conclusion, to enhance the job performance of outsourced employees, it is important for management to examine and improve the various factors related to job satisfaction. Additonally, for outsourced employees to have organizational commitments to the hiring and client companies simultaneously, management should emphasize a sense of unity and share organizational values.

• The Research Journal of the Costume Culture
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• v.19 no.2
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• pp.360-375
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• 2011

The fashion market focuses on consumers and maximizes consumers' satisfaction. The fashion market has been segmented to better satisfy the variety of consumer group. Although market segmentation has been studied, efficiency and effectiveness of market segmentation continuously bring problems. Also, problems of prediction about real consumer behavior, and efficiency and effectiveness of standards are pointed out. The purpose of this study is to determine the most important variables for dividing fashion product buyers. This study was designed as qualitative study and in-depth interview was conducted. The in-depth interview was conducted with five experts in fashion intelligence agency. In-depth interview was completed by an analytic induction and an investigator triangulation. Questions were about characteristics, demographic characteristics, important factors and fashion buying relationship, and interests of current clothing shoppers. The results of qualitative research demonstrated that clothing shoppers, with their valuable consumption and selective buying behaviors, seek differentiated products. They also long for high quality apparel for its price, because of their valuable consumption and price centered tendency. They illustrated active sides, such as enthusiastic information searching and emotional or experiential consumption, rather than attitudinal sides. The variables for dividing fashion product buyers included: "innovative seeking", "symbolic seeking", "personalized seeking", "quality-seeking", "selective seeking", "price-seeking", "utility-seeking", "hedonic seeking", "sensitive seeking", "brand-seeking", "digital seeking", "information-seeking", and "eco-seeking".

• Journal of Families and Better Life
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• v.27 no.4
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• pp.41-54
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• 2009

This study focused on the ecological variables that affect adolescents' runway impulse. For the organisms, self-esteem, impulse control, school achievement and runway experience, for the microsystems, family, school and peer environment, for the mesosystems, family-peer relationships and family-school relationships, and for the exosystem, neighborhood environment were included. The sample consisted of 651 eleventh grade adolescents. Instruments were the Runway Impulse Scale(Nam, 2001) and Index of organisms, microsystems, mesosystems, and exosystem variables. Statistics and methods used for the analysis were Cronbach's alpha, frequency, percentage, t-test, Pearson's correlation and multiple Regression. Several major results were found from the analysis. First, no sex difference was found in adolescents' runway impulse. Second, runway impulse of male and female adolescents showed positive correlations with runway experience, parental marital conflict, dissatisfactions of school life and exposure to friends with problems behavior but negative correlations with self-esteem, impulse control, school achievement, parental support and supervision, teacher support, family-peer relationships and neighborhood environment. Female adolescents' runway impulse stowed negative correlations with family-school relationships. Third, the most important variable predicting male adolescents' runway impulse was exposure to friends with problems behavior, the most important variable for female was self-esteem.

• The Research Journal of the Costume Culture
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• v.7 no.6
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• pp.28-40
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• 1999

The purpose of this study was to understand the Korean teenagers\` clothing behavior through pointing out the factors that clothing behavior of teenagers that was initiated from the important reference group, TV stars. The subject of this study were 570 purposively selected students at female middle and high school students in Seoul. The results were as follows : 1. The clothing conformity to TV stars relating to demographic variables was influenced significantly by location and personal expense variable in the high school group. 2. The exhibition showed a more important role to the clothing conformity in middle school group than in high school group. 3. The clothing conformity to TV stars relating to the clothing related variables was significantly affected by self-confidence to clothing than clothing normative recognition, clothing risk recognition and degree of clothing importance regardless of groups. 4. The clothing conformity to TV stars relating to TV media variables was affected by TV media star identification variable in both groups. And in case of middle school group, interests in TV stars also had influence on the clothing conformity to TV stars. And in case of high school group, interests in TV had effect on the imitation to TV stars\` clothing. As middle school students tend to have self-identification about a particular person, TV media stars become the reference group for the adolescence to follow their clothing.