• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.219-241
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• 1999

This study used the Data Envelopment Analysis, a mathematical linear programming method, to evaluate cost efficiency of hospitals in Korea. DEA method was applied to 244 hospitals: 31 bankrupt hospitals and 213 survived hospitals. Among the 213 sound hospitals, 11 hospitals showed efficiency score 100, but more than 40 hospitals recorded efficiency scores lower than 60. This result implies that more hospitals can be bankrupt in the restructuring process of the industry within 1-2 years. Among the 31 bankrupt hospitals, the highest technical efficiency score was 0.821 and 11 hospitals showed technical efficiency lower than 0.6. This implies that selective financial support based on cost efficiency by the government will be valuable to prevent bankruptcy of these hospitals. The logistic analysis showed statistically significant relationship between bankruptcy and efficiency of hospitals in Korea.

• International Journal of Human Ecology
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• v.10 no.2
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• pp.13-24
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• 2009

The effects of grandparenting involvement and emotional attachments on emotional and behavioral development among adolescents were explored through the use of a UK cross-sectional national data of 1,566 adolescents aged eleven to sixteen years old receiving some form of grandparenting. A correlation and logistic regression analyses yielded results that supported the positive effects of grandparenting on the emotional and behavioral disorder symptoms of adolescents. The results indicate that most selected socio-demographic, grandparenting involvement, and the emotional attachment variables of grandchildren influenced the likelihood of increasing or decreasing emotional disorder symptoms among adolescents. However, no support was found for perceiving emotional attachments with grandparents as a predictor of behavioral disorder symptoms among youth, whereas socio-demographic and grandparenting involvement variables showed significant impacts on behavioral disorder symptoms. The findings highlight the importance of a systematic approach about the socio-demographic characteristics, levels of grandparenting, and emotional attachment levels with grandparents to understand youth cared for by grandparents that experience emotional and/or behavioral disorder symptoms, when intervention or prevention programs are considered.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.133-154
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• 2010

Recently, Internet Telephony has become increasingly popular in telecommunication industry. However, previous research on Internet Telephony has focused on analyzing specific Internet Telephonysolutions, identifyingthe Internet Telephony movement itself. The research on prediction models about Internet Telephony adoption has been minimal. The main propose of this study is to develop models for predicting transition intention from using traditional telephones to using Internet Telephony. To do so, this study uses data mining methods to analyze demands in the IT communications market and to provide management strategies for Internet telephony providers. Especially this study uses discriminant analysis, logistic regression, classification tree, and neural nets to develop those prediction models toward Internet Telephony adoption. The models are compared with each other and a superior model is chosen.

• Environmental Engineering Research
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• v.19 no.2
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• pp.117-122
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• 2014

Indexes of safety, restoration, damage impact, and management reliability were developed to assess reliability of drinking water distribution networks (DWDNs) management. The developed indexes were applied to evaluate the reliability of the pipeline management stage during unexpected mechanical and hydraulic accidents of components. The results were used to support the decision-making process in effective management and maintenance by enhancing the administrator's system understanding and by helping to create appropriate maintenance and management policies. The results of this study indicated that application of a management reliability index to assess DWDNs reliability may help create a more effective plan for establishing DWDNs management and maintenance.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.7-8
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• 2018

This study proposes an analysis of the Word2vec-based machine learning classifiers for the sake of opinion mining tasks. As a bench-marking method, BOW (Bag-of-Words) was adopted. On the basis of utilizing the Word2vec and BOW as feature extraction methods, we applied Laptop and Restaurant dataset to LR, DT, SVM, RF classifiers. The results showed that the Word2vec feature extraction yields more improved performance.

• Research in Community and Public Health Nursing
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• v.30 no.1
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• pp.90-98
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• 2019

Purpose: The purpose of this study is to identify the association between maternal feeding practices and excessive weight gain in infants. Methods: This study adopted a cross-sectional design and included 240 pairs of mothers and their infants (129 boys and 111 girls) in public healthcare centers in the Daejeon area in South Korea. Via multivariate analyses, the association between maternal feeding practices and excessive weight gain in infants was identified. Results: Among 240 infants in this study, 39 (16.3%) infants gained excessive weight during 12 months after birth. Using multivariate logistic regression with adjustment for covariates, more than 7 months of exclusive breastfeeding was associated with a reduced likelihood of excessive weight gain in infants during the 12 months after birth (adjusted odds ratio: 0.39, 95% confidence interval: 0.02~0.81, p=.029). Conclusion: Based on these results, nurses in communities and clinics should educate mothers on the importance of longer durations of exclusive breast feeding and develop strategies for encouraging such behavior. Furthermore, support for exclusive breast feeding should be provided in various settings.

• Journal of Korean Public Health Nursing
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• v.34 no.3
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• pp.380-390
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• 2020

Purpose: The study was undertaken to determine the socio-ecological convergence factors affecting on attempts to quit smoking in out-of-school youths. Methods: The study participants were 187 out-of-school youths enrolled Youth support Centers, collected from November 2018 to February 2019, analyzed through x2test and independent sample t-test, logistic regression analysis. Results: There was a significant differences and associated within daily smoking amounts, age of start smoking, intense physical activity, intake breakfast, smoking cessation self-efficiency, and smoking attitude among socio-ecological characteristics according to attempts of quit-smoking. Conclusion: The results of this study will be provided a basic data for developing The Quit-Smoking Intervention Program for out-of-school youth's health activities.

• Analyses & Alternatives
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• v.4 no.1
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• pp.105-123
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• 2020

This study analyzes the risk selection behavior of Japanese households. The study approaches the view of 'the hyperbolic discount' which is used in behavioral economics based on the rise in mortgage lending by low-income households in the late 2000s. The study focuses on how households risk preferences vary by income levels. The study analyzes the relationship of attitude of household interest rate risk using Binomial Logistic and Heckman two-step estimation method assuming that there are only two types of Adjustable-Rate Mortgage and Fixed-Rate Mortgage. As a result of the empirical analysis, low-income households annual income tend to have a higher proportion of housing debt as same as higher interest rate risk preferences households in proportion to income growth and interest rate risk preferences. Those results indicate that there is possibility of a hyperbolic discount on low-income households in Japan, and support the hypothesis that low-income households are relatively higher household debt ratio because of high utility due to home purchase in the near future (short-term).

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.186-191
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• 2023

Neural Networks are widely used for huge variety of tasks solution. Machine Learning methods are used also for signal and time series analysis, including electrocardiograms. Contemporary wearable devices, both medical and non-medical type like smart watch, allow to gather the data in real time uninterruptedly. This allows us to transfer these data for analysis or make an analysis on the device, and thus provide preliminary diagnosis, or at least fix some serious deviations. Different methods are being used for this kind of analysis, ranging from medical-oriented using distinctive features of the signal to machine learning and deep learning approaches. Here we will demonstrate a neural network-based approach to this task by building an ensemble of 1D CNN classifiers and a final classifier of selection using logistic regression, random forest or support vector machine, and make the conclusions of the comparison with other approaches.

• SUVANNABHUMI
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• v.11 no.1
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• pp.101-132
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• 2019

Why do some local rebel groups choose to form asymmetric alliances with large transnational terrorist organizations? This paper examines asymmetric terrorist alliance patterns by studying the international ties of domestic insurgencies in Southeast Asia. It uses data from Indonesia, Malaysia, the Philippines, and Thailand to construct a theory defining the determinants of the choice of alliance strategies by terrorist groups. The findings conclude that rebels with limited aims prefer to act alone out of fear of entrapment. They are cautious of becoming associated with the struggle of transnational radical groups and provoking organized response from international and regional counterterrorism authorities. Local groups are more likely to seek alliance with an established movement when they have ambitious final objectives, challenging the core interests of the target state. In this case, the benefits of training and logistic support provided by an experienced organization outweigh the costs of becoming a target for coordinated counterterrorist campaign.