• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6180-6189
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• 2015

The purpose of this study is to clarify the factors that affects smartphone addiction of elementary school students. The subjects were 263 students, from 4 elementary schools located in G-city. Data were collected from July, 2014 and analyzed using SPSS 19.0 program. The prevalence of addiction risk group and non-addicted group were 16.0% and 84.0%, respectively. The variables which had statistically significant differences with smart phone addiction of general characteristics are grade, living together family, economic status, school record, motivation for usage, advantage of usage and using time (p<.05). There was pure correlation between the smartphone addiction and impulsivity (r=.496, p<.001), daily stress (r=.471, p<.001). However, perceived parental attitude (r=-.375, p<.001) and self-esteem (r=-.444, p<.001) were inverse correlation with smartphone addiction. Higher using time, higher impulsivity and higher daily stress were all associated with increased of smartphone addiction level. These results suggest that more attentions should be given to early adolescents and could be effectively used as fundamental data to develop intervention programs, which can prevent the smartphone addiction.

• The Journal of Korean Society for School & Community Health Education
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• v.22 no.4
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• pp.39-48
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• 2021

Objectives: The purpose is to prepare measures to effectively improve college life adaptation by identifying relevance between interpersonal relation disposition and college life adaptation, college life stress and college life adaptation for dental hygiene students. Methods: 375 dental hygiene students attending some local universities in Gyeonggi-do were sampled for convenience. The results of this study are as follows. Results: First, As a result of interpersonal relation disposition according to general characteristics, superiority-dominance tendencies were higher in first and third graders, in groups with grades above 4.0 and groups with lower subjective economic levels. And the stress of college life was high for second graders and students with lower grades than 2.0. Second, According to the correlation between factors, governance-dominance, independence-responsibility, sympathy-acceptance, sociable-friendliness, and ostentation-intoxication of interpersonal tendency factors had proportional relationship with college life adaptation, rebellion-distrust and college life stress had inverse relationship. Third, The results of multiple regression analyses to identify factors that affect college students' adaptation to college life were in the order of stress in college life, first grade, sociable-friendliness, second grade, rebellion-distrust. Conclusion: In order to improve college life adaptation, counseling and practical mediation programs should be developed and applied to effectively manage and control the negativity and positivity implied by interpersonal relationships and college life stress.

• International Area Studies Review
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• v.16 no.3
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• pp.323-341
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• 2012

In the recent year, the urbanization is emerging as important issue for sustainable development in China. Like the most of the world, urbanization of China is closely related with the domestic market development, the innovation of industrial structure, and the reduction of income cap among regions, urban-rural region and so on. This paper analyzes the impact of urbanization on economic growth using cross section data and time series data of the eastern coastal regions in China. Based on the existing literature, we establish a hypothesis, which is basically the same as Williamson(1965)'s hypothesis, that urbanization promotes the economic growth at the early stages of development but has adverse effects in economies that have reached a certain income level. The results of study are as follows: Using 10-provinces data of the eastern coastal region in China, this paper examines the impact of urbanization on economic growth. Regression results suggest that Williamson's hypothesis is not verified, regardless of estimation methods in two models. Hence, the results show that the impact of urbanization on economic growth has not the inverse U-type function in the eastern coastal region of China.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.835-842
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• 2018

The so-called sliced average variance estimation (SAVE) is a popular methodology in sufficient dimension reduction literature. SAVE is sensitive to the number of slices in practice. To overcome this, a fused SAVE (FSAVE) is recently proposed by combining the kernel matrices obtained from various numbers of slices. In the paper, we consider practical applications of FSAVE to large p-small n data. For this, near-infrared spectroscopy of biscuit dough data is analyzed. In this case study, the usefulness of FSAVE in high-dimensional data analysis is confirmed by showing that the result by FASVE is superior to existing analysis results.

• Korean Journal of Clinical Pharmacy
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• v.30 no.4
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• pp.264-269
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• 2020

Background: Inflammatory diseases can increase the prevalence of anemia. Recent studies confirmed that the prevalence of anemia is increased by atopic dermatitis (AD), a chronic inflammatory disease. Therefore, we aimed to elucidate the correlation between AD severity and prevalence of anemia. Methods: We used data of pediatric patients from the Health Insurance Review and Assessment Service (HIRA-PPS-2016). We included pediatric patients (<18 years) with AD diagnosis who were prescribed medications for AD. We applied a propensity score method with inverse probability of treatment weighting (IPTW) adjusting for differences in prevalence of confounders and performed IPTW logistic regression to evaluate associations between the anemia and severity of AD. Results: In total, 91,501 patients (mild AD: 47,054 patients; moderate-to-severe AD: 44,447 patients) <18 years who were prescribed drugs for AD were analyzed. Analysis of the probability of patients with mild AD and prevalence of anemia as a reference revealed an odds ratio (OR) of 1.159 (95% CI, 1.109-1.212; p<0.001) in moderate-to-severe AD patients, indicating a correlation between anemia prevalence and AD severity. Subgroup analysis according to gender, age group, and type of health insurance revealed there was an association between AD severity and anemia except in patients equal or older than 7 years. Conclusion: The prevalence of anemia increased with AD severity despite adjusting for confounding factors. Our results support the hypothesis that AD can cause anemia, and anemia prevalence could be increased in severe AD patients. Further studies are needed to establish a pathological basis.

• Korean Journal of Community Nutrition
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• v.25 no.6
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• pp.512-519
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• 2020

Objectives: A cross-sectional study was conducted to investigate the associations between food groups and hearing loss. Methods: Data of 1,312 individuals were used from the Korea National Health and Nutrition Examination Survey 2013. Hearing loss was determined with a pure tone average (PTA) of greater than 25 dB in either ear. The PTA was measured as the average hearing threshold at speech frequencies of 0.5, 1, 2, and 4 kHz. The dietary intake was examined with a food frequency questionnaire with 112 food items. The food items were classified into 25 food groups. A weighted logistic regression was used to investigate the association. Results: Individuals in the highest tertile of vegetables and nuts food groups were less likely to have hearing loss than those in the lowest tertile [Odds Ratio (OR) = 0.58 (95% Confidence interval (CI) 0.38-0.91), P = 0.019; OR = 0.59 (95% CI 0.39-0.90), P = 0.020, respectively], after adjusting for confounding variables of age, sex, body mass index, drinking, smoking, diabetes, hypertension, and physical activity. Conclusions: In this cross-sectional study, we observed that high intake of vegetables and nuts food groups revealed significant inverse associations with hearing loss, after adjusting for confounding variables among 1,312 participants.

• Journal of Yeungnam Medical Science
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• v.39 no.1
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• pp.24-30
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• 2022

Background: Texture analysis has been used as a method for quantifying image properties based on textural features. The aim of the present study was to evaluate the usefulness of magnetic resonance imaging (MRI) texture analysis for the evaluation of viable ovarian tissue on the perfusion map of ovarian endometriosis. Methods: To generate a normalized perfusion map, subtracted T1-weighted imaging (T1WI), T1WI and contrast-enhanced T1W1 with sequences were performed using the same parameters in 25 patients with surgically confirmed ovarian endometriosis. Integrated density is defined as the sum of the values of the pixels in the image or selection. We investigated the parameters for texture analysis in ovarian endometriosis, including angular second moment (ASM), contrast, correlation, inverse difference moment (IDM), and entropy, which is equivalent to the product of area and mean gray value. Results: The perfusion ratio and integrated density of normal ovary were 0.52±0.05 and 238.72±136.21, respectively. Compared with the normal ovary, the affected ovary showed significant differences in total size (p<0.001), fractional area ratio (p<0.001), and perfusion ratio (p=0.010) but no significant differences in perfused tissue area (p=0.158) and integrated density (p=0.112). In comparison of parameters for texture analysis between the ovary with endometriosis and the contralateral normal ovary, ASM (p=0.004), contrast (p=0.002), IDM (p<0.001), and entropy (p=0.028) showed significant differences. A linear regression analysis revealed that fractional area had significant correlations with ASM (r²=0.211), IDM (r²=0.332), and entropy (r²=0.289). Conclusion: MRI texture analysis could be useful for the evaluation of viable ovarian tissues in patients with ovarian endometriosis.

• Journal of Korea Trade
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• v.27 no.1
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• pp.101-118
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• 2023

Purpose - Korea became a trillion-dollar trading country in 2011. With the exponential increase in Korea's trade volume over the past decades, trade-related administrative burdens per capita for Korea Customs became enormous, for which the government established the Single Window, a trade-facilitating system, in 2004 to enhance the efficiency of customs-clearing procedures for traders. This paper focuses on finding whether the Korean Single Window system affects the country's trade facilitation positively through an empirical methodology. Design/methodology - To find empirical evidence that Single Window affects trade facilitation for the customs-clearing procedure, this study assumes that a time-efficient environment enables the handling of the increase in trade volume, under which four independent variables related to import customs-clearing procedures and two dependent variables to import were adopted for empirical analysis. The import customs procedures are classified into four steps from port entry to declaration acceptance. To understand the relationship between variables, scattered plots and correlation coefficients were calculated. Eight hypotheses were set and underwent simple linear regression. The data for analysis were collected by Korea Customs, and were about the lead time of import, the volume of imports in million USD, and the number of import declarations reported to customs offices on a monthly basis from 2005 to 2013. Findings - Six of the eight hypotheses showed the statistically significant result that lead time in the import customs-clearing procedure positively affects the number of import declaration reports and import volume. Specifically, Hypothesis 1, Hypothesis 2, and Hypothesis 3 strongly support the assumption lead time in import customs declaration has an inverse relationship with the number of import declarations, which means that the shorter the import lead time, the more import declaration increases. Research Limitations/Implications - With limited data accessibility to the government's custom-sclearing procedures, only the import lead time for customs clearance were adopted as independent variables. This paper, however, successfully found that the Single Window system contributed to trade facilitation. Originality/value - This study found that the time-saving Single Window system of Korea Customs enables itself to manage an exponentially-increasing trade volume by creating a trade-facilitating environment for customs personnel and traders, which may be a unique implication found through quantitative methodology.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.139-148
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• 2024

In the post-pandemic era, the demand for online education platforms has surged, leading to increased consumer reliance on online reviews for decision-making. This study investigates the impact of Chinese online customer reviews on consumer purchase behavior in online education. By examining the role of trust, review sentiment, and the quantity and timeliness of reviews, the research aims to understand how these factors influence consumer decisions. By using regression model, findings reveal that negative reviews, timely feedback, and a higher volume of reviews positively affect consumer purchase decisions, while course pricing demonstrates an inverse relationship. Furthermore, cognitive and affective trust mediate the relationship between reviews and purchase behavior, highlighting a reverse U-shaped effect on consumer decision inclination. These insights provide valuable implications for online education providers, emphasizing the need to manage and leverage online reviews to foster consumer trust and improve sales performance.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.108-117
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• 2024

The selection and recommendation of a suitable job applicant from the pool of thousands of applications are often daunting jobs for an employer. The recommendation and selection process significantly increases the workload of the concerned department of an employer. Thus, Resume Classification System using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process and ease the job of an employer. Moreover, the automation of this process can significantly expedite and transparent the applicants' selection process with mere human involvement. Nevertheless, various Machine Learning approaches have been proposed to develop Resume Classification Systems. However, this study presents an automated NLP and ML-based system that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of Resume Classification Systems and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP & ML techniques for processing & classification of Resumes, the extracted features were tested on nine machine learning models Support Vector Machine - SVM (Linear, SGD, SVC & NuSVC), Naïve Bayes (Bernoulli, Multinomial & Gaussian), K-Nearest Neighbor (KNN) and Logistic Regression (LR). The Term-Frequency Inverse Document (TF-IDF) feature representation scheme proven suitable for Resume Classification Task. The developed models were evaluated using F-Score_M, Recall_M, Precission_M, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume Classification task, the SVM class of Machine Learning algorithms performed better on the study dataset with over 96% overall accuracy. The promising results suggest that NLP & ML techniques employed in this study could be used for the Resume Classification task.